Machine Learning Jobs in Dubai

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.We are looking for a Sr. AI Engineer to join our GenAI Squad, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.5+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator, and communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

About the company:We’re not just part of the travel industry, we’re helping shape its future.As Saudi Arabia’s leading travel company, we serve millions across every segment of the travel and tourism ecosystem.Rooted in our name “Almosafer,” meaning the traveler, we strive to make every journey seamless, personal, and purposeful. Our diverse platforms and services are built to deliver enriching experiences that reflect the spirit of Saudi Arabia and the wider region.We’re united by a bold vision:To be the undisputed leader in travel services, fostering lasting connections and setting new benchmarks for excellence in the Kingdom and beyond. Our team across Saudi Arabia and the wider region blends deep cultural understanding with forward-thinking innovation, shaping a new standard for travel in the region. About the role:We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.Responsibilities:Design, build, and deploy machine learning models and algorithms.Collaborate with data scientists to refine data features and enhance model performance.Optimize and improve existing machine learning models for efficiency and accuracy.Conduct data preprocessing, feature engineering, and data analysis.Monitor and maintain models in production to ensure they operate effectively.Document and communicate model designs and performance metrics to stakeholders.Stay updated on the latest industry trends and advancements in machine learning and AI.Participate in code reviews and contribute to a culture of continuous improvement. Profile Requirements:Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field4+ years of experience as a Machine Learning Engineer or in a similar role.Proficiency in programming languages such as Python, Java, or R.Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn).Strong understanding of algorithms, data structures, and software engineering principles.Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models.Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).Excellent problem-solving skills and ability to work collaboratively in a team environment.Experience with deep learning and natural language processing (NLP) techniques.Understanding of model interpretability and explainability.Perform statistical analysis, and train and retrain systems to optimize performance.Preferred Skills:Familiarity with version control systems (e.g., Git) and CI/CD practices.Experience with AI/GenAIExperience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena)Design/build and deploy API services Being you @ Almosafer:At Almosafer, our teams work with purpose, clarity, and a shared commitment to doing things the right way. Whether you're building platforms, supporting travelers, or shaping strategy, your work connects to something bigger. Across functions and locations, we value accountability, trust, and collaboration - and we create the structure and space for you to contribute meaningfully from day one.Here, you will find:A purpose-led workplace where your ideas can create real impactOngoing learning and development to help you grow with intentionRecognition that celebrates your wins, both big and smallA community built on trust, curiosity, and shared momentumNo matter where your journey started, at Almosafer, you will find space to grow, connect, and contribute meaningfully. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.We are looking for a Sr. AI Engineer to join our GenAI Squad, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.5+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator, and communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

Quantitative Researcher — Systematic StrategiesUAE | Full-timeHiring for a world-leading institutional investor building out a quant research division and dedicated AI/ML research lab. Significant compute resources, long time horizons, and serious capital behind systematic strategies.The Role Develop alpha signals and systematic strategies using ML, deep learning, and statistical techniques across equities, rates, FX, and multi-asset. Take research from ideation to production. Collaborate with PMs, engineers, and data teams.YouPhD or equivalent in ML, statistics, maths, CS, or quant financeExperience building trading signals in a live environmentPython required, C++ a plusWhy HereMassive investment in quant and AI capabilitiesScale and resources few firms can matchLong-horizon research culture - not chasing quarterly P&LUAE - tax-free, high quality of lifeAll applications confidential Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.We are looking for a Sr. AI Engineer to join our GenAI Squad, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.5+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator, and communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

About UsTamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.Your RoleWe are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.Your ResponsibilitiesModel Deployment & ScalingProductionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architecturesDesign low-latency, high-availability APIs and pipelines for real-time model inference.Implement batch scoring systems for periodic risk assessments.=MLOps & InfrastructureBuild and maintain CI/CD pipelines for model deployment and monitoring.Set up automated feature engineering pipelines, leveraging feature stores.Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.Model Monitoring & MaintenanceImplement real-time and batch monitoring for data drift, concept drift, and model performance.Build automated retraining workflows and model rollback mechanisms.Collaboration with Risk DSWork closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.Advise DS on efficient model architectures for operational environments.Optimize feature computation for speed and scalability.System Design & IntegrationIntegrate models with credit underwriting, fraud detection, collections, and merchant risk systems.Collaborate with backend engineering to align on API contracts and system interfaces.Your Expertise6+ years of experience as an MLE, ML Engineer, Mlops Developer.Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).Proven track record of deploying and maintaining ML models in production at scale.Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).All qualified individuals are encouraged to apply. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Senior Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 5+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

About UsTamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.Your RoleWe are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.Your ResponsibilitiesModel Deployment & ScalingProductionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architecturesDesign low-latency, high-availability APIs and pipelines for real-time model inference.Implement batch scoring systems for periodic risk assessments.=MLOps & InfrastructureBuild and maintain CI/CD pipelines for model deployment and monitoring.Set up automated feature engineering pipelines, leveraging feature stores.Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.Model Monitoring & MaintenanceImplement real-time and batch monitoring for data drift, concept drift, and model performance.Build automated retraining workflows and model rollback mechanisms.Collaboration with Risk DSWork closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.Advise DS on efficient model architectures for operational environments.Optimize feature computation for speed and scalability.System Design & IntegrationIntegrate models with credit underwriting, fraud detection, collections, and merchant risk systems.Collaborate with backend engineering to align on API contracts and system interfaces.Your Expertise6+ years of experience as an MLE, ML Engineer, Mlops Developer.Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).Proven track record of deploying and maintaining ML models in production at scale.Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).All qualified individuals are encouraged to apply. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

Quantitative Researcher — Systematic StrategiesUAE | Full-timeHiring for a world-leading institutional investor building out a quant research division and dedicated AI/ML research lab. Significant compute resources, long time horizons, and serious capital behind systematic strategies.The Role Develop alpha signals and systematic strategies using ML, deep learning, and statistical techniques across equities, rates, FX, and multi-asset. Take research from ideation to production. Collaborate with PMs, engineers, and data teams.YouPhD or equivalent in ML, statistics, maths, CS, or quant financeExperience building trading signals in a live environmentPython required, C++ a plusWhy HereMassive investment in quant and AI capabilitiesScale and resources few firms can matchLong-horizon research culture - not chasing quarterly P&LUAE - tax-free, high quality of lifeAll applications confidential Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Quantitative Researcher — Systematic StrategiesUAE | Full-timeHiring for a world-leading institutional investor building out a quant research division and dedicated AI/ML research lab. Significant compute resources, long time horizons, and serious capital behind systematic strategies.The Role Develop alpha signals and systematic strategies using ML, deep learning, and statistical techniques across equities, rates, FX, and multi-asset. Take research from ideation to production. Collaborate with PMs, engineers, and data teams.YouPhD or equivalent in ML, statistics, maths, CS, or quant financeExperience building trading signals in a live environmentPython required, C++ a plusWhy HereMassive investment in quant and AI capabilitiesScale and resources few firms can matchLong-horizon research culture - not chasing quarterly P&LUAE - tax-free, high quality of lifeAll applications confidential Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About UsTamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.Your RoleWe are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.Your ResponsibilitiesModel Deployment & ScalingProductionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architecturesDesign low-latency, high-availability APIs and pipelines for real-time model inference.Implement batch scoring systems for periodic risk assessments.=MLOps & InfrastructureBuild and maintain CI/CD pipelines for model deployment and monitoring.Set up automated feature engineering pipelines, leveraging feature stores.Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.Model Monitoring & MaintenanceImplement real-time and batch monitoring for data drift, concept drift, and model performance.Build automated retraining workflows and model rollback mechanisms.Collaboration with Risk DSWork closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.Advise DS on efficient model architectures for operational environments.Optimize feature computation for speed and scalability.System Design & IntegrationIntegrate models with credit underwriting, fraud detection, collections, and merchant risk systems.Collaborate with backend engineering to align on API contracts and system interfaces.Your Expertise6+ years of experience as an MLE, ML Engineer, Mlops Developer.Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).Proven track record of deploying and maintaining ML models in production at scale.Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).All qualified individuals are encouraged to apply. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

Quantitative Researcher — Systematic StrategiesUAE | Full-timeHiring for a world-leading institutional investor building out a quant research division and dedicated AI/ML research lab. Significant compute resources, long time horizons, and serious capital behind systematic strategies.The Role Develop alpha signals and systematic strategies using ML, deep learning, and statistical techniques across equities, rates, FX, and multi-asset. Take research from ideation to production. Collaborate with PMs, engineers, and data teams.YouPhD or equivalent in ML, statistics, maths, CS, or quant financeExperience building trading signals in a live environmentPython required, C++ a plusWhy HereMassive investment in quant and AI capabilitiesScale and resources few firms can matchLong-horizon research culture - not chasing quarterly P&LUAE - tax-free, high quality of lifeAll applications confidential Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a ML Engineer 3 who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer 3 (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action.We need people with the courage to be fiercely original.noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

About UsTamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.Your RoleWe are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.Your ResponsibilitiesModel Deployment & ScalingProductionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architecturesDesign low-latency, high-availability APIs and pipelines for real-time model inference.Implement batch scoring systems for periodic risk assessments.=MLOps & InfrastructureBuild and maintain CI/CD pipelines for model deployment and monitoring.Set up automated feature engineering pipelines, leveraging feature stores.Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.Model Monitoring & MaintenanceImplement real-time and batch monitoring for data drift, concept drift, and model performance.Build automated retraining workflows and model rollback mechanisms.Collaboration with Risk DSWork closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.Advise DS on efficient model architectures for operational environments.Optimize feature computation for speed and scalability.System Design & IntegrationIntegrate models with credit underwriting, fraud detection, collections, and merchant risk systems.Collaborate with backend engineering to align on API contracts and system interfaces.Your Expertise6+ years of experience as an MLE, ML Engineer, Mlops Developer.Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).Proven track record of deploying and maintaining ML models in production at scale.Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).All qualified individuals are encouraged to apply. Show more Show less

Social Discovery Group (SDG) is one of the world's largest groups of social discovery companies, uniting millions of users on dozens of products. SDG solves the problem of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG products redefine the way people interact and connect with each other.Our portfolio includes social entertainment platforms designed to connect people online across different cultures in different parts of the world. This includes globally recognized brands such as DateMyAge, Dating.com, EuroDate, Dil Mil and Cupid Media. SDG has a presence in more than 150 countries.We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1000+ professionals and digital nomads works all over the world. Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations.We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025).We are looking for a Senior ML Engineer to join one of our core AI teams and work on a large-scale AI product with hundreds of thousands of active users.This role is for a strong hands-on ML engineer who enjoys working with modern LLM systems, multimodal models, and production AI pipelines. You will work on building and improving large-scale machine learning systems, developing data pipelines, and experimenting with cutting-edge generative AI technologies.Your Main Tasks Will BeDesign and build production-grade ML systems, including LLM-based applications and AI agentsDevelop and maintain scalable data pipelines for training and evaluating machine learning modelsWork with large multimodal datasets (text, images, video) and build efficient data processing workflowsImprove model quality, evaluation pipelines, and automated metricsImplement and optimize training and inference pipelines, including GPU optimization where neededExperiment with modern generative AI approaches, including LLMs and multimodal modelsCollaborate closely with engineers and product teams to deliver robust ML solutions in productionContinuously improve system performance, reliability, and scalabilityWe Expect From You5+ years of hands-on experience in Machine Learning / AI engineeringStrong Python programming skills and experience building production systemsExperience working with LLMs, generative AI, or modern deep learning modelsExperience building data pipelines and processing large datasetsExperience with distributed data processing frameworks (Ray, Spark, Dask, or similar)Solid understanding of model training, evaluation, and optimization techniquesAbility to take ownership of solutions end-to-end and work independentlyStrong problem-solving skills and ability to operate in a fast-paced environmentWhat Do We OfferREMOTE OPPORTUNITY to work full time;Vacation 28 calendar days per year;7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;Bonuses up to $5000 for recommending successful applicants for positions in the company;50% payment for professional training, international conferences and meetings;Corporate discount for English lessons; Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About the CompanyCareem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.Careem’s ML Platform & GenAI Applications team sits at the intersection of engineering, data science, and product innovation. We provide the core tooling that lets every vertical — Ride-Hailing, Food, Groceries, Pay, and more; deliver intelligent, delightful experiences powered by Machine Learning and Generative AI. As a Senior Software Engineer on this team you’ll be a hands-on technical leader: designing distributed systems, hardening new GenAI workflows, and making it effortless for product teams to move from prototype to production while meeting Careem-class standards for reliability, cost-efficiency, and responsible AI.What You'll DoDesign and build reusable services, APIs, and workflows that make it simple for product teams to prototype, test, and launch GenAI-driven featuresCo-create flagship GenAI applications for example, RAG-powered help-centre answers, driver-partner copilots, or marketplace-level demand forecasting assistantsInfluence architecture: keep the platform reliable, secure, and cost-effective while adding new capabilities like prompt versioning, model evaluation dashboards, or real-time feedback loopsChampion MLOps & Responsible AI, establish guardrails, monitoring, and safe-launch practices so experiments can reach production with confidenceMentor teammates and share learnings through design reviews, mini-workshops, and internal demosCollaborate widely with designers, product managers, and data scientists to convert fuzzy product ideas into well-scoped engineering workWhat You’ll Need7+ years of hands-on experience in software development with solid foundation in principles and design practicesStrong expertise in Python, Java, Go, or similar programming languagesHands-on experience with GenAI and ML platforms—fine-tuning transformers, managing embeddings, or rolling out RAG pipelinesWorking knowledge of vector databases (Pinecone, Milvus, Weaviate) and model-aware searchStrong foundations in software design, networking, security, observability, and CI/CDExperience with cloud control planes (AWS, GCP, etc.) or database internals, including query optimizationProven ability to drive projects from inception to production and mentor other engineersExperience with ML platform and MLOps is a must Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Social Discovery Group (SDG) is one of the world's largest groups of social discovery companies, uniting millions of users on dozens of products. SDG solves the problem of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG products redefine the way people interact and connect with each other.Our portfolio includes social entertainment platforms designed to connect people online across different cultures in different parts of the world. This includes globally recognized brands such as DateMyAge, Dating.com, EuroDate, Dil Mil and Cupid Media. SDG has a presence in more than 150 countries.We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1000+ professionals and digital nomads works all over the world. Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations.We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025).We are looking for a Senior ML Engineer to join one of our core AI teams and work on a large-scale AI product with hundreds of thousands of active users.This role is for a strong hands-on ML engineer who enjoys working with modern LLM systems, multimodal models, and production AI pipelines. You will work on building and improving large-scale machine learning systems, developing data pipelines, and experimenting with cutting-edge generative AI technologies.Your Main Tasks Will BeDesign and build production-grade ML systems, including LLM-based applications and AI agentsDevelop and maintain scalable data pipelines for training and evaluating machine learning modelsWork with large multimodal datasets (text, images, video) and build efficient data processing workflowsImprove model quality, evaluation pipelines, and automated metricsImplement and optimize training and inference pipelines, including GPU optimization where neededExperiment with modern generative AI approaches, including LLMs and multimodal modelsCollaborate closely with engineers and product teams to deliver robust ML solutions in productionContinuously improve system performance, reliability, and scalabilityWe Expect From You5+ years of hands-on experience in Machine Learning / AI engineeringStrong Python programming skills and experience building production systemsExperience working with LLMs, generative AI, or modern deep learning modelsExperience building data pipelines and processing large datasetsExperience with distributed data processing frameworks (Ray, Spark, Dask, or similar)Solid understanding of model training, evaluation, and optimization techniquesAbility to take ownership of solutions end-to-end and work independentlyStrong problem-solving skills and ability to operate in a fast-paced environmentWhat Do We OfferREMOTE OPPORTUNITY to work full time;Vacation 28 calendar days per year;7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;Bonuses up to $5000 for recommending successful applicants for positions in the company;50% payment for professional training, international conferences and meetings;Corporate discount for English lessons; Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

We’re working with a Silicon Valley–origin AI company focused on taking AI out of notebooks and into production.This role sits at the intersection of machine learning, infrastructure, and reliability.The team is responsible for making sure AI systems are deployable, observable, scalable, and cost-efficient across cloud and hybrid environments.If you enjoy turning models into real, reliable systems, this role is built for that.What you’ll doDeploy and operate ML models in production environmentsBuild and maintain CI/CD pipelines for ML workloadsManage model serving, monitoring, logging, and alertingWork with backend and platform teams to productionize AI systemsImprove reliability, performance, and cost efficiency of AI deploymentsWhat we’re looking forExperience as an MLOps Engineer, ML Engineer, or Platform EngineerStrong understanding of Kubernetes, containers, and cloud infrastructureExperience with model deployment, serving, and monitoringFamiliarity with CI/CD, infrastructure-as-code, and automationComfortable owning production systems end-to-endNice to haveExperience with on-prem or hybrid AI deploymentsFamiliarity with model optimization, inference performance, or GPU workloadsExperience working with large-scale AI or data platforms Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

About the CompanyCareem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.Careem’s ML Platform & GenAI Applications team sits at the intersection of engineering, data science, and product innovation. We provide the core tooling that lets every vertical — Ride-Hailing, Food, Groceries, Pay, and more; deliver intelligent, delightful experiences powered by Machine Learning and Generative AI. As a Senior Software Engineer on this team you’ll be a hands-on technical leader: designing distributed systems, hardening new GenAI workflows, and making it effortless for product teams to move from prototype to production while meeting Careem-class standards for reliability, cost-efficiency, and responsible AI.What You'll DoDesign and build reusable services, APIs, and workflows that make it simple for product teams to prototype, test, and launch GenAI-driven featuresCo-create flagship GenAI applications for example, RAG-powered help-centre answers, driver-partner copilots, or marketplace-level demand forecasting assistantsInfluence architecture: keep the platform reliable, secure, and cost-effective while adding new capabilities like prompt versioning, model evaluation dashboards, or real-time feedback loopsChampion MLOps & Responsible AI, establish guardrails, monitoring, and safe-launch practices so experiments can reach production with confidenceMentor teammates and share learnings through design reviews, mini-workshops, and internal demosCollaborate widely with designers, product managers, and data scientists to convert fuzzy product ideas into well-scoped engineering workWhat You’ll Need7+ years of hands-on experience in software development with solid foundation in principles and design practicesStrong expertise in Python, Java, Go, or similar programming languagesHands-on experience with GenAI and ML platforms—fine-tuning transformers, managing embeddings, or rolling out RAG pipelinesWorking knowledge of vector databases (Pinecone, Milvus, Weaviate) and model-aware searchStrong foundations in software design, networking, security, observability, and CI/CDExperience with cloud control planes (AWS, GCP, etc.) or database internals, including query optimizationProven ability to drive projects from inception to production and mentor other engineersExperience with ML platform and MLOps is a must Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

Social Discovery Group (SDG) is one of the world's largest groups of social discovery companies, uniting millions of users on dozens of products. SDG solves the problem of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG products redefine the way people interact and connect with each other.Our portfolio includes social entertainment platforms designed to connect people online across different cultures in different parts of the world. This includes globally recognized brands such as DateMyAge, Dating.com, EuroDate, Dil Mil and Cupid Media. SDG has a presence in more than 150 countries.We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1000+ professionals and digital nomads works all over the world. Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations.We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025).We are looking for a Senior ML Engineer to join one of our core AI teams and work on a large-scale AI product with hundreds of thousands of active users.This role is for a strong hands-on ML engineer who enjoys working with modern LLM systems, multimodal models, and production AI pipelines. You will work on building and improving large-scale machine learning systems, developing data pipelines, and experimenting with cutting-edge generative AI technologies.Your Main Tasks Will BeDesign and build production-grade ML systems, including LLM-based applications and AI agentsDevelop and maintain scalable data pipelines for training and evaluating machine learning modelsWork with large multimodal datasets (text, images, video) and build efficient data processing workflowsImprove model quality, evaluation pipelines, and automated metricsImplement and optimize training and inference pipelines, including GPU optimization where neededExperiment with modern generative AI approaches, including LLMs and multimodal modelsCollaborate closely with engineers and product teams to deliver robust ML solutions in productionContinuously improve system performance, reliability, and scalabilityWe Expect From You5+ years of hands-on experience in Machine Learning / AI engineeringStrong Python programming skills and experience building production systemsExperience working with LLMs, generative AI, or modern deep learning modelsExperience building data pipelines and processing large datasetsExperience with distributed data processing frameworks (Ray, Spark, Dask, or similar)Solid understanding of model training, evaluation, and optimization techniquesAbility to take ownership of solutions end-to-end and work independentlyStrong problem-solving skills and ability to operate in a fast-paced environmentWhat Do We OfferREMOTE OPPORTUNITY to work full time;Vacation 28 calendar days per year;7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;Bonuses up to $5000 for recommending successful applicants for positions in the company;50% payment for professional training, international conferences and meetings;Corporate discount for English lessons; Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Futurise Training Institute is expanding into cutting-edge technologies and we’re looking for an experienced AI & Machine Learning Trainer to join our team in Dubai Knowledge Park!If you’re passionate about Artificial Intelligence, Large Language Models (LLMs), and Agentic AI—and enjoy sharing your knowledge—this is your chance to make an impact.🔹 Role: AI & Machine Learning Trainer (Part-Time / Freelance)🔹 Location: Dubai (Online & In-Person sessions)💡 What we’re looking for:✔️ Strong expertise in AI, Machine Learning & Algorithms✔️ Hands-on experience with LLMs, Prompt Engineering & Agentic AI✔️ Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.)✔️ Prior teaching/training experience is a must✔️ Ability to simplify complex concepts into practical learning✨ Join us in shaping the next generation of AI professionals!📩 Apply now by sending your CV and project portfolio to hr@futurise.ae Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

About UsTamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.Your RoleWe are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.Your ResponsibilitiesModel Deployment & ScalingProductionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architecturesDesign low-latency, high-availability APIs and pipelines for real-time model inference.Implement batch scoring systems for periodic risk assessments.=MLOps & InfrastructureBuild and maintain CI/CD pipelines for model deployment and monitoring.Set up automated feature engineering pipelines, leveraging feature stores.Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.Model Monitoring & MaintenanceImplement real-time and batch monitoring for data drift, concept drift, and model performance.Build automated retraining workflows and model rollback mechanisms.Collaboration with Risk DSWork closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.Advise DS on efficient model architectures for operational environments.Optimize feature computation for speed and scalability.System Design & IntegrationIntegrate models with credit underwriting, fraud detection, collections, and merchant risk systems.Collaborate with backend engineering to align on API contracts and system interfaces.Your Expertise6+ years of experience as an MLE, ML Engineer, Mlops Developer.Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).Proven track record of deploying and maintaining ML models in production at scale.Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).All qualified individuals are encouraged to apply. Show more Show less

Job DescriptionAbout AgodaAt Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.Agoda is an online travel booking platform for accommodation, flights, and more. We build and deploy cutting edge technology that connects travelers with more than 2.5 million accommodations globally. Based in Asia and part of Booking Holdings, our 4,000+ talents coming from 90+ different nationalities foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enabling our customers to experience the world.Get to Know Our TeamThe Engineering department oversees all Agoda’s ML and software related requirements. Our goal is to enable and increase Agoda’s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company’s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.Why Agoda Engineering Team (ML role)?Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API’s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.This role is based in Gurgaon, India. In This Role, You Will Get ToLead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.Build, administer and scale ML processing pipelines.Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etcDesign, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.What You’ll need to Succeed:Bachelor’s degree in computer science /information systems/engineering/related field8+ years of experience in software engineering with a minimum of 4+ years in MLGood experience in PysparkExpert level understanding of Python with design patterns and object-oriented programming.Experience debugging and reasoning about production issues is desirable.A good understanding of data architecture principles preferred.Any other experience with Big Data technologies / toolsSQL experienceAnalytical problem-solving capabilities & experience.Systems administration skills in LinuxA strong engineering driven mindset will be required to succeed in this role.It’s great if you have:Good understanding of Hadoop ecosystemsExperience working with Open-source productsExperience with Scala developmentWorking in an agile environment using test driven methodologiesBenefitsHybrid Working ModelWFH Set Up Allowance30 Days of Remote Working from anywhere globally every yearEmployee discount for accommodation globallyGlobal team of 90+ nationalities40+ offices and 25+ countriesAnnual CSR / Volunteer Time offBenevity Subscription for employee donationsVolunteering opportunities globallyFree Headspace subscriptionFree Odilo & Udemy subscriptionsAccess to Employee Assistance Program (third party for personal and workplace support)Enhanced Parental LeaveLife, TPD & Accident Insurance#telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #budapest #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #osaka #malta #amsterdam #oslo #warsaw #krakow #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #bangalore #delhi #hyderabad #pune #singapore #beijing #shanghai #shenzhen #tokyo #seoul #hongkong #taipei #kualalumpur #jakarta #hochiminh #hochiminhcity #manila #instanbul #makati #dubai #riyadh #gurgaon #noidaDiscover More About Working At AgodaAgoda Careers https://careersatagoda.comFacebook https://www.facebook.com/agodacareers/LinkedIn https://www.linkedin.com/company/agodaYouTube https://www.youtube.com/agodalifeEqual Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.DisclaimerWe do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.Job DetailsRole Level: Mid-Level Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://careersatagoda.com/ Job Function: Information Technology (IT) Company Industry/Sector: Technology Information and InternetWhat We OfferAbout The CompanySearching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.ReportDisclaimer: talentmate.com is only a platform to bring jobseekers & employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com. Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

About noon We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a (add title) who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.As a Machine Learning Engineer III (MLE3), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesWhat you'll do:Deeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamMentor junior engineers and promote a culture of technical excellence and rigorWhat you'll need:Experience: 3-5+ years of hands-on experience in Machine Learning; experience in e-commerce or ad-tech is highly preferredSystem Contribution: Experience contributing to the design and implementation of large-scale ML systems and infrastructureProduction Focus: Experience working in high-scale, latency-sensitive environmentsDomain Expertise: A strong understanding of ranking, forecasting, and candidate diversityTech Stack: Experience with cloud platforms (GCP / Vertex AI is a significant plus).Who will excel?We’re looking for people with high standards, who understand that hard work matters.You need to be relentlessly resourceful and operate with a deep bias for action. We need people with the courage to be fiercely original. noon is not for everyone; readiness to adapt, pivot, and learn is essential. Show more Show less

Competitive Salary, Plus BenefitsCharterhouse is working with a specialist AI consultancy based in the UAE that partners with enterprise clients to deliver and implement cutting-edge Generative AI solutions. As part of continued growth, they are looking to expand their delivery team with the addition of a Principal AI/ML Engineer.The Principal AI/ML Engineer will take ownership of architecting and delivering intelligent AI solutions and workflows, leveraging Python, PyTorch, and modern generative AI frameworks to build production-grade solutions. The role involves fine-tuning models using approaches such as LoRA, qLoRA, and full fine-tuning, optimising prompts, embeddings, and retrieval strategies, and building and deploying retrieval-augmented generation (RAG) solutions. The Principal Engineer will also oversee and contribute to developing custom pipelines for document ingestion, chunking, embedding generation, and retrieval, working with vector databases and RAG evaluation frameworks.Beyond model development and deployment, the role also requires a strong understanding of AI performance and deep learning optimisation. The Principal Engineer will profile and benchmark AI workloads across hardware platforms, experiment with model compression techniques including quantization, pruning, and knowledge distillation, and bring a working knowledge of how deep learning frameworks such as PyTorch and TensorFlow behave at a lower level. Given the complexity of enterprise AI deployments, hands-on experience deploying and optimising AI workloads across GPU, TPU, or NPU infrastructure is strongly preferred.The ideal candidate will bring strong software engineering foundations including testing, debugging, documentation, and version control, alongside experience with MLOps tooling such as ClearML, Kubeflow, or MLflow and data analysis libraries including Pandas, NumPy, and SQL.A strong foundation in large language models (LLMs) is essential for this role, with the ideal candidate bringing hands-on experience across multiple LLMs and a solid understanding of how different models can be applied and optimised for domain-specific use cases. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Role DescriptionPlay a techno-functional role - combine business with understanding of data and machine learning tools to lead workstreams and projects of low to medium complexityHandle large volume of data for generating business insights for the clientsWork independently on analytical platforms like SAS, Python etc.Work independently to manage data using platforms like SQL, Oracle, SAS and ability to develop data pipelinesWork with the team to deliver on client engagement. Actively participate in client meetings and deliver client presentations independently to mid level managementProblem solve technical and business issues with the team. For example how to define an event in a model or logic of the program that will extract the data from client system and load into the model martSolid understanding of Banking IndustrySkill SetExcellent problem solving and client communication / client management skillsAt least 36 months of relevant work experience into any of the domains - big data, financial crimes and forensics, risk management, marketing analyticsPrior experience in advanced analytivs, data and technology is a must. Knowledge in SAS, Python, R or any other analytical platform is importantHands on experience of working with large scale data through at least simple SQL queriesAbility to work in teamsNever say die attitude and openness to work in unstructured business environment Show more Show less

AI/ML Engineer – Generative AI & Agentic SystemsRole OverviewWe are seeking an experienced AI/ML Engineer with strong expertise in Python, Generative AI,and Agentic AI systems to design, develop, and deploy intelligent AI solutions. The idealcandidate has hands‑on experience building AI agents, LLM-powered applications, andend‑to‑end machine learning pipelines.Key Responsibilities Build, fine‑tune, and optimize Large Language Models (LLMs). Develop RAG pipelines and prompt engineering strategies. Design multi-step autonomous AI agents and workflows. Build ML models and maintain ML pipelines in Python. Write scalable, production‑ready Python code. Integrate AI capabilities into apps and cloud platforms. Hands on Azure and AWS Infrastucture deploymentsRequired Skills & Experience Strong proficiency in Python (NumPy, pandas, FastAPI, LangChain,PyTorch/TensorFlow). Expertise in Generative AI (GenAI) and LLM tools. Experience building AI Agents and Agentic AI workflows. Knowledge of embeddings, vector DBs, and model evaluation. ML fundamentals, MLOps, and production deployment.Preferred Qualifications Experience with enterprise AI agents or automation workflows. Knowledge of Azure ML, AWS Sagemaker, or Vertex AI. Experience designing agent frameworks and memory modules. Minimum 5 years of hand on experience Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

MissionAre you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you!About UsAily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models, and agentic AI to give business leaders clear, actionable insights in real time.Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, NY and now Dubai. Our mission is to democratize AI in business and enable leaders to Lead Boldly , turning complex data into decisions that drive real, measurable impact.We are looking for AI/ML Engineers who are passionate about the power of AI and love building robust AI/ML systems: people who turn models into reliable, scalable products, and ensure our AI solutions are production-ready, efficient and impactful. Your job is to build and scale the AI/ML infrastructure and pipelines that power Aily’s decision intelligence platform.About This Team - AI PlatformThe AI Platform team is the backbone of Aily’s decision intelligence. We design, build, and operate libraries, tools, and the shared AI/ML infrastructure that enables AI & Data teams to empower business-critical decision-making for our enterprise users.Our 3 missions are to enable innovation at scale, to minimize entropy, and to accelerate progress for Aily.If you enjoy working at the intersection of AI and software, closely collaborating & empowering other teams, setting technical direction, and turning complexity into leverage, this team is the right place to make your mark.Your profileCore responsibilities (by seniority)Mid AI/ML Engineer - 3+ years of experiencePartner with Data Scientists and Engineers to bring AI solutions to productionDesign and implement end-to-end ML pipelines (data→model→deployment→monitoring) autonomouslyContribute to APIs, tools, and libraries used by more than 100 AI team members daily (including Cloud & LLM Infrastructure and AI-driven features)Communicate with your team: present results and findings, identify gaps and opportunities, and learn to explain our product and software/AI behindRequirements: Solid AI/ML fundamentals, strong Python, APIs/K8s/Docker/Cloud experience, mentor junior team members on technical topicsSenior AI/ML Engineer - 4+ years of experienceAll of the above +Own complex projects, lead technical initiatives from design to implementation (refactoring, standardization)Ensure the quality of your own and your teams' developmentsInteract with other functions and agree on exchange protocols and architecture design (DevOps, Front End, Data Engineering, Back End, …)Sponsor the creation and implementation of new software and ML standards in the AI teamRequirements: Strong software engineering practices, Deep AI/ML knowledge, outstanding problem-solving skills, ability and willingness to lead and mentor Junior team membersPrincipal AI/ML Engineer - 6+ years of experienceAll of the above +Shape AI Platform strategy across teams and be a technical reference for Aily’s AI teamLead cross-team design sessions, define, enforce, and maintain org-wide standards"Make things happen" at scale, manage leadership pressureLead a team of 4+ AI/ML Engineers and own their roadmapRequirements: Driven by impact and value, able to lead multiple technical initiatives in parallel, mastery in the modern AI/ML stack (AWS, FastAPI, Docker, K8s, Python, CI/CD, Airflow, Agentic coding, concurrency, etc)Who we’re looking for (all levels)You are impact-driven and thrive at the intersection of AI, business, ML engineering, and product. You want to build real systems that power decision-making at scale.A builder: you enjoy shipping reliable solutions, improving systems and tooling, and making things work in production at scale.A strong collaborator who enjoys working with Data Scientists, Product Managers, and Engineers, and can explain trade-offs and designs in simple terms.Someone with a startup mindset: comfortable with ambiguity, proactive, hands-on, and willing to improve things beyond your immediate scope.Ready to Lead Boldly - helping Aily and its customers scale AI systems that enable faster, smarter decisions every day.Applicants must already have the legal right to work in SpainLocation & detailsLocations: DubaiContract type: PermanentAbout UsLEARN MORE Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

What started in 2007 with a pizza and a plan has grown into a fast-moving SaaS company empowering manufacturers, distributors, and wholesalers to thrive in complex B2B commerce. Our mission is simple: help businesses build stronger relationships through seamless digital commerce. At Sana Commerce, we're looking for a Data Engineer (ML/AI) to design, build, and scale data systems that power our analytics and machine learning initiatives. Your work will ensure high-quality, reliable, and ML-ready data pipelines that enable both traditional analytics and advanced AI-driven solutions across the business.Job DescriptionWhat you'll be doingDesigning and maintaining data pipelines optimized for ML/AI workloads, including handling of large-scale, unstructured, and semi-structured data. Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models. Collaborating with Data Scientists and ML Engineers to understand data requirements for training, validation, and production deployment. Ensuring data quality, lineage, and governance meet standards required for AI/ML applications. Supporting MLOps practices by integrating data pipelines with model training, monitoring, and deployment workflows. Leveraging distributed processing frameworks (e.g., Spark, Databricks, Azure Synapse) for scalable ML data processing. QualificationsWhat you bring8+ years of experience as a Data Engineer, working with Azure and Databricks, ideally with exposure to ML/AI-related data workflows. College degree that demonstrates your analytic abilities, such as Econometrics, Computer Sciences, Mathematics or similar;Excellent analytical and problem-solving skills;Experience with data preparation for ML/AI: managing large datasets, feature engineering, and real-time or batch data pipelines. Familiarity with MLOps concepts and how data engineering supports model lifecycle management. Experience with orchestration frameworks (Airflow, Prefect, or Azure Data Factory) for complex ML pipelines. Knowledge of unstructured data processing (text, images, logs) is a plus. Strong SQL and Python skills; experience with distributed data processing (PySpark, Dask, etc.) is a plus. Why you’ll love working hereImpact from day one – Join a scale-up where your ideas shape how global businesses operate online. Continuous learning – Access a structured onboarding rated 9.1/10 by previous hires, mentorship, and feedback culture. Hybrid flexibility – Work from our office 3 days per week and from home 2 days. Career growth – Expand your technical and leadership scope in a company built for long-term success. Our valuesAt Sana Commerce, our values drive everything we do:Champions of Our League – We deliver lasting success, balancing quick wins and long-term valueSupercharge Our Customers – We’re revolutionizing B2B commerce together, helping our customers to lead and succeed.Determined to Grow – We embrace challenges, growing and raising the bar for ourselves and our industry.Bold Together – We dare to be bold because we have each other’s back.Ready to build reliability that scales?Apply now and help shape the foundation of our next-generation SaaS platform.Additional Information Show more Show less

Social Discovery Group (SDG) is the 3rd largest social discovery company in the world, uniting 60+ brands with 500 million users. We solve the problems of loneliness, isolation, and disconnection by transforming virtual intimacy into the new normal. Our portfolio includes online communication platforms focusing on AI, game mechanics, and video streaming - Dating.com, DateMyAge, Cupid Media, Dil Mil, Kiseki, and others.SDG invests in IT startups around the world. Our investments include Open AI, Patreon, Flo, Clubhouse, Woebot, Flure, Astry, Coursera, Academia.edu, and many others.We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1200 professionals and digital nomads works all over the world.Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations. In August 2024, we achieved Great Place to Work US Certification™! This achievement reflects our core belief that a truly exceptional workplace is built on trust, pride, and camaraderie—not just great perks.We are looking for a Senior ML Engineer to join one of our core AI teams and work on a large-scale AI product with hundreds of thousands of active users.This role is for a strong hands-on ML engineer who enjoys working with modern LLM systems, multimodal models, and production AI pipelines. You will work on building and improving large-scale machine learning systems, developing data pipelines, and experimenting with cutting-edge generative AI technologies.Your Main Tasks Will BeDesign and build production-grade ML systems, including LLM-based applications and AI agentsDevelop and maintain scalable data pipelines for training and evaluating machine learning modelsWork with large multimodal datasets (text, images, video) and build efficient data processing workflowsImprove model quality, evaluation pipelines, and automated metricsImplement and optimize training and inference pipelines, including GPU optimization where neededExperiment with modern generative AI approaches, including LLMs and multimodal modelsCollaborate closely with engineers and product teams to deliver robust ML solutions in productionContinuously improve system performance, reliability, and scalabilityWe Expect From You5+ years of hands-on experience in Machine Learning / AI engineeringStrong Python programming skills and experience building production systemsExperience working with LLMs, generative AI, or modern deep learning modelsExperience building data pipelines and processing large datasetsExperience with distributed data processing frameworks (Ray, Spark, Dask, or similar)Solid understanding of model training, evaluation, and optimization techniquesAbility to take ownership of solutions end-to-end and work independentlyStrong problem-solving skills and ability to operate in a fast-paced environmentWhat Do We OfferREMOTE OPPORTUNITY to work full time;Vacation 28 calendar days per year;7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;Bonuses up to $5000 for recommending successful applicants for positions in the company;50% payment for professional training, international conferences and meetings;Corporate discount for English lessons; Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Job DescriptionAbout AgodaAt Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.Agoda is an online travel booking platform for accommodation, flights, and more. We build and deploy cutting edge technology that connects travelers with more than 2.5 million accommodations globally. Based in Asia and part of Booking Holdings, our 4,000+ talents coming from 90+ different nationalities foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enabling our customers to experience the world.Get to Know Our TeamThe Engineering department oversees all Agoda’s ML and software related requirements. Our goal is to enable and increase Agoda’s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company’s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.Why Agoda Engineering Team (ML role)?Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API’s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.This role is based in Gurgaon, India. In This Role, You Will Get ToLead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.Build, administer and scale ML processing pipelines.Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etcDesign, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.What You’ll need to Succeed:Bachelor’s degree in computer science /information systems/engineering/related field8+ years of experience in software engineering with a minimum of 4+ years in MLGood experience in PysparkExpert level understanding of Python with design patterns and object-oriented programming.Experience debugging and reasoning about production issues is desirable.A good understanding of data architecture principles preferred.Any other experience with Big Data technologies / toolsSQL experienceAnalytical problem-solving capabilities & experience.Systems administration skills in LinuxA strong engineering driven mindset will be required to succeed in this role.It’s great if you have:Good understanding of Hadoop ecosystemsExperience working with Open-source productsExperience with Scala developmentWorking in an agile environment using test driven methodologiesBenefitsHybrid Working ModelWFH Set Up Allowance30 Days of Remote Working from anywhere globally every yearEmployee discount for accommodation globallyGlobal team of 90+ nationalities40+ offices and 25+ countriesAnnual CSR / Volunteer Time offBenevity Subscription for employee donationsVolunteering opportunities globallyFree Headspace subscriptionFree Odilo & Udemy subscriptionsAccess to Employee Assistance Program (third party for personal and workplace support)Enhanced Parental LeaveLife, TPD & Accident Insurance#telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #budapest #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #osaka #malta #amsterdam #oslo #warsaw #krakow #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #bangalore #delhi #hyderabad #pune #singapore #beijing #shanghai #shenzhen #tokyo #seoul #hongkong #taipei #kualalumpur #jakarta #hochiminh #hochiminhcity #manila #instanbul #makati #dubai #riyadh #gurgaon #noidaDiscover More About Working At AgodaAgoda Careers https://careersatagoda.comFacebook https://www.facebook.com/agodacareers/LinkedIn https://www.linkedin.com/company/agodaYouTube https://www.youtube.com/agodalifeEqual Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.DisclaimerWe do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.Job DetailsRole Level: Mid-Level Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://careersatagoda.com/ Job Function: Information Technology (IT) Company Industry/Sector: Technology Information and InternetWhat We OfferAbout The CompanySearching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.ReportDisclaimer: talentmate.com is only a platform to bring jobseekers & employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

Key Responsibilities:•Build and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring.•Automate model workflows using CI/CD and Continuous Training (CT) principles.•Develop and manage reusable pipeline templates for LLM fine-tuning, RAG deployments, and multi-agent orchestration.•Optimize cloud resource usage for efficient large-model training and inference•Lead ML model lifecycle automation including CI/CD pipelines, monitoring, and production deployments•Establish MLOps best practices for model versioning, automated testing, and continuous deployment•Manage inference endpoints for real-time and batch predictions across environments (Dev, Staging, Prod).•Implement model monitoring for drift detection, performance degradation, and latency tracking•Manage feature stores, data versioning, and lineage tracking for reproducibility.•Collaborate with AI engineers and data scientists to optimize model training and deployment workflows•Drive adoption of DevOps practices in ML teams including infrastructure as code and automated deployments•Design security and compliance frameworks for ML infrastructure and model governance•Manage cost optimization and resource allocation for ML training and inference workloads•Work closely with AI Architects, ML Engineers, and DevOps to improve pipeline reliability. Position MLOPs Engineer I Section Data & AI Division e& enterprise.Qualifications & Experience:•Emirati with Family book•Male candidates must have completed the National service.•Bachelor's or Engineering degree in Computer Science, Data Science, or related technical field.•2+ years of experience in DevOps, platform engineering, or ML infrastructure•Knowledge of Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure)•Strong experience with Infrastructure as Code tools (Terraform, CloudFormation) and CI/CD pipelines; MLOps tools knowledge like Airflow, Kubeflow, MLflow etc. Show more Show less

MissionAre you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you!About UsAily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models, and agentic AI to give business leaders clear, actionable insights in real time.Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, NY and now Dubai. Our mission is to democratize AI in business and enable leaders to Lead Boldly , turning complex data into decisions that drive real, measurable impact.We are looking for AI/ML Engineers who are passionate about the power of AI and love building robust AI/ML systems: people who turn models into reliable, scalable products, and ensure our AI solutions are production-ready, efficient and impactful. Your job is to build and scale the AI/ML infrastructure and pipelines that power Aily’s decision intelligence platform.About This Team - AI PlatformThe AI Platform team is the backbone of Aily’s decision intelligence. We design, build, and operate libraries, tools, and the shared AI/ML infrastructure that enables AI & Data teams to empower business-critical decision-making for our enterprise users.Our 3 missions are to enable innovation at scale, to minimize entropy, and to accelerate progress for Aily.If you enjoy working at the intersection of AI and software, closely collaborating & empowering other teams, setting technical direction, and turning complexity into leverage, this team is the right place to make your mark.Your profileCore responsibilities (by seniority)Mid AI/ML Engineer - 3+ years of experiencePartner with Data Scientists and Engineers to bring AI solutions to productionDesign and implement end-to-end ML pipelines (data→model→deployment→monitoring) autonomouslyContribute to APIs, tools, and libraries used by more than 100 AI team members daily (including Cloud & LLM Infrastructure and AI-driven features)Communicate with your team: present results and findings, identify gaps and opportunities, and learn to explain our product and software/AI behindRequirements: Solid AI/ML fundamentals, strong Python, APIs/K8s/Docker/Cloud experience, mentor junior team members on technical topicsSenior AI/ML Engineer - 4+ years of experienceAll of the above +Own complex projects, lead technical initiatives from design to implementation (refactoring, standardization)Ensure the quality of your own and your teams' developmentsInteract with other functions and agree on exchange protocols and architecture design (DevOps, Front End, Data Engineering, Back End, …)Sponsor the creation and implementation of new software and ML standards in the AI teamRequirements: Strong software engineering practices, Deep AI/ML knowledge, outstanding problem-solving skills, ability and willingness to lead and mentor Junior team membersPrincipal AI/ML Engineer - 6+ years of experienceAll of the above +Shape AI Platform strategy across teams and be a technical reference for Aily’s AI teamLead cross-team design sessions, define, enforce, and maintain org-wide standards"Make things happen" at scale, manage leadership pressureLead a team of 4+ AI/ML Engineers and own their roadmapRequirements: Driven by impact and value, able to lead multiple technical initiatives in parallel, mastery in the modern AI/ML stack (AWS, FastAPI, Docker, K8s, Python, CI/CD, Airflow, Agentic coding, concurrency, etc)Who we’re looking for (all levels)You are impact-driven and thrive at the intersection of AI, business, ML engineering, and product. You want to build real systems that power decision-making at scale.A builder: you enjoy shipping reliable solutions, improving systems and tooling, and making things work in production at scale.A strong collaborator who enjoys working with Data Scientists, Product Managers, and Engineers, and can explain trade-offs and designs in simple terms.Someone with a startup mindset: comfortable with ambiguity, proactive, hands-on, and willing to improve things beyond your immediate scope.Ready to Lead Boldly - helping Aily and its customers scale AI systems that enable faster, smarter decisions every day.Applicants must already have the legal right to work in SpainLocation & detailsLocations: DubaiContract type: PermanentAbout UsLEARN MORE Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

About AgodaAt Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.Agoda is an online travel booking platform for accommodation, flights, and more. We build and deploy cutting edge technology that connects travelers with more than 2.5 million accommodations globally. Based in Asia and part of Booking Holdings, our 4,000+ talents coming from 90+ different nationalities foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enabling our customers to experience the world.Get to Know Our TeamThe Engineering department oversees all Agoda’s ML and software related requirements. Our goal is to enable and increase Agoda’s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company’s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.Why Agoda Engineering Team (ML role)?Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API’s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.This role is based in Gurgaon, India. In this Role, you will get to: Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes. Build, administer and scale ML processing pipelines. Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc. Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etc Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality. Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks. We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.What You’ll need to Succeed: Bachelor’s degree in computer science /information systems/engineering/related field 8+ years of experience in software engineering with a minimum of 4+ years in ML Good experience in Pyspark Expert level understanding of Python with design patterns and object-oriented programming. Experience debugging and reasoning about production issues is desirable. A good understanding of data architecture principles preferred. Any other experience with Big Data technologies / tools SQL experience Analytical problem-solving capabilities & experience. Systems administration skills in Linux A strong engineering driven mindset will be required to succeed in this role.It’s great if you have: Good understanding of Hadoop ecosystems Experience working with Open-source products Experience with Scala development Working in an agile environment using test driven methodologiesBenefitsHybrid Working ModelWFH Set Up Allowance30 Days of Remote Working from anywhere globally every yearEmployee discount for accommodation globallyGlobal team of 90+ nationalities40+ offices and 25+ countriesAnnual CSR / Volunteer Time offBenevity Subscription for employee donationsVolunteering opportunities globallyFree Headspace subscriptionFree Odilo & Udemy subscriptionsAccess to Employee Assistance Program (third party for personal and workplace support)Enhanced Parental LeaveLife, TPD & Accident Insurance#telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #budapest #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #osaka #malta #amsterdam #oslo #warsaw #krakow #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #bangalore #delhi #hyderabad #pune #singapore #beijing #shanghai #shenzhen #tokyo #seoul #hongkong #taipei #kualalumpur #jakarta #hochiminh #hochiminhcity #manila #instanbul #makati #dubai #riyadh #gurgaon #noidaDiscover More About Working At AgodaAgoda Careers https://careersatagoda.comFacebook https://www.facebook.com/agodacareers/LinkedIn https://www.linkedin.com/company/agodaYouTube https://www.youtube.com/agodalifeEqual Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.DisclaimerWe do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

MissionAre you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you!About UsAily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models, and agentic AI to give business leaders clear, actionable insights in real time.Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, NY and now Dubai. Our mission is to democratize AI in business and enable leaders to Lead Boldly , turning complex data into decisions that drive real, measurable impact.We are looking for AI/ML Engineers who are passionate about the power of AI and love building robust AI/ML systems: people who turn models into reliable, scalable products, and ensure our AI solutions are production-ready, efficient and impactful. Your job is to build and scale the AI/ML infrastructure and pipelines that power Aily’s decision intelligence platform.About This Team - AI PlatformThe AI Platform team is the backbone of Aily’s decision intelligence. We design, build, and operate libraries, tools, and the shared AI/ML infrastructure that enables AI & Data teams to empower business-critical decision-making for our enterprise users.Our 3 missions are to enable innovation at scale, to minimize entropy, and to accelerate progress for Aily.If you enjoy working at the intersection of AI and software, closely collaborating & empowering other teams, setting technical direction, and turning complexity into leverage, this team is the right place to make your mark.Your profileCore responsibilities (by seniority)Mid AI/ML Engineer - 3+ years of experiencePartner with Data Scientists and Engineers to bring AI solutions to productionDesign and implement end-to-end ML pipelines (data→model→deployment→monitoring) autonomouslyContribute to APIs, tools, and libraries used by more than 100 AI team members daily (including Cloud & LLM Infrastructure and AI-driven features)Communicate with your team: present results and findings, identify gaps and opportunities, and learn to explain our product and software/AI behindRequirements: Solid AI/ML fundamentals, strong Python, APIs/K8s/Docker/Cloud experience, mentor junior team members on technical topicsSenior AI/ML Engineer - 4+ years of experienceAll of the above +Own complex projects, lead technical initiatives from design to implementation (refactoring, standardization)Ensure the quality of your own and your teams' developmentsInteract with other functions and agree on exchange protocols and architecture design (DevOps, Front End, Data Engineering, Back End, …)Sponsor the creation and implementation of new software and ML standards in the AI teamRequirements: Strong software engineering practices, Deep AI/ML knowledge, outstanding problem-solving skills, ability and willingness to lead and mentor Junior team membersPrincipal AI/ML Engineer - 6+ years of experienceAll of the above +Shape AI Platform strategy across teams and be a technical reference for Aily’s AI teamLead cross-team design sessions, define, enforce, and maintain org-wide standards"Make things happen" at scale, manage leadership pressureLead a team of 4+ AI/ML Engineers and own their roadmapRequirements: Driven by impact and value, able to lead multiple technical initiatives in parallel, mastery in the modern AI/ML stack (AWS, FastAPI, Docker, K8s, Python, CI/CD, Airflow, Agentic coding, concurrency, etc)Who we’re looking for (all levels)You are impact-driven and thrive at the intersection of AI, business, ML engineering, and product. You want to build real systems that power decision-making at scale.A builder: you enjoy shipping reliable solutions, improving systems and tooling, and making things work in production at scale.A strong collaborator who enjoys working with Data Scientists, Product Managers, and Engineers, and can explain trade-offs and designs in simple terms.Someone with a startup mindset: comfortable with ambiguity, proactive, hands-on, and willing to improve things beyond your immediate scope.Ready to Lead Boldly - helping Aily and its customers scale AI systems that enable faster, smarter decisions every day.Applicants must already have the legal right to work in SpainLocation & detailsLocations: DubaiContract type: PermanentAbout UsLEARN MORE Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Key Responsibilities:•Build and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring.•Automate model workflows using CI/CD and Continuous Training (CT) principles.•Develop and manage reusable pipeline templates for LLM fine-tuning, RAG deployments, and multi-agent orchestration.•Optimize cloud resource usage for efficient large-model training and inference•Lead ML model lifecycle automation including CI/CD pipelines, monitoring, and production deployments•Establish MLOps best practices for model versioning, automated testing, and continuous deployment•Manage inference endpoints for real-time and batch predictions across environments (Dev, Staging, Prod).•Implement model monitoring for drift detection, performance degradation, and latency tracking•Manage feature stores, data versioning, and lineage tracking for reproducibility.•Collaborate with AI engineers and data scientists to optimize model training and deployment workflows•Drive adoption of DevOps practices in ML teams including infrastructure as code and automated deployments•Design security and compliance frameworks for ML infrastructure and model governance•Manage cost optimization and resource allocation for ML training and inference workloads•Work closely with AI Architects, ML Engineers, and DevOps to improve pipeline reliability. Position MLOPs Engineer I Section Data & AI Division e& enterprise.Qualifications & Experience:•Emirati with Family book•Male candidates must have completed the National service.•Bachelor's or Engineering degree in Computer Science, Data Science, or related technical field.•2+ years of experience in DevOps, platform engineering, or ML infrastructure•Knowledge of Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure)•Strong experience with Infrastructure as Code tools (Terraform, CloudFormation) and CI/CD pipelines; MLOps tools knowledge like Airflow, Kubeflow, MLflow etc. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Social Discovery Group (SDG) is the 3rd largest social discovery company in the world, uniting 60+ brands with 500 million users. We solve the problems of loneliness, isolation, and disconnection by transforming virtual intimacy into the new normal. Our portfolio includes online communication platforms focusing on AI, game mechanics, and video streaming - Dating.com, DateMyAge, Cupid Media, Dil Mil, Kiseki, and others.SDG invests in IT startups around the world. Our investments include Open AI, Patreon, Flo, Clubhouse, Woebot, Flure, Astry, Coursera, Academia.edu, and many others.We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1200 professionals and digital nomads works all over the world.Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations. In August 2024, we achieved Great Place to Work US Certification™! This achievement reflects our core belief that a truly exceptional workplace is built on trust, pride, and camaraderie—not just great perks.We are looking for a Senior ML Engineer to join one of our core AI teams and work on a large-scale AI product with hundreds of thousands of active users.This role is for a strong hands-on ML engineer who enjoys working with modern LLM systems, multimodal models, and production AI pipelines. You will work on building and improving large-scale machine learning systems, developing data pipelines, and experimenting with cutting-edge generative AI technologies.Your Main Tasks Will BeDesign and build production-grade ML systems, including LLM-based applications and AI agentsDevelop and maintain scalable data pipelines for training and evaluating machine learning modelsWork with large multimodal datasets (text, images, video) and build efficient data processing workflowsImprove model quality, evaluation pipelines, and automated metricsImplement and optimize training and inference pipelines, including GPU optimization where neededExperiment with modern generative AI approaches, including LLMs and multimodal modelsCollaborate closely with engineers and product teams to deliver robust ML solutions in productionContinuously improve system performance, reliability, and scalabilityWe Expect From You5+ years of hands-on experience in Machine Learning / AI engineeringStrong Python programming skills and experience building production systemsExperience working with LLMs, generative AI, or modern deep learning modelsExperience building data pipelines and processing large datasetsExperience with distributed data processing frameworks (Ray, Spark, Dask, or similar)Solid understanding of model training, evaluation, and optimization techniquesAbility to take ownership of solutions end-to-end and work independentlyStrong problem-solving skills and ability to operate in a fast-paced environmentWhat Do We OfferREMOTE OPPORTUNITY to work full time;Vacation 28 calendar days per year;7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;Bonuses up to $5000 for recommending successful applicants for positions in the company;50% payment for professional training, international conferences and meetings;Corporate discount for English lessons; Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

🚀 Machine Learning Architect (LLMs & Agentic AI) | Fintech Startup | Dubai (Hybrid)We’re working with a well-funded fintech startup in Dubai building intelligent, AI-native financial products across trading, automation, and decisioning. As part of their next growth phase, they’re hiring a senior, hands-on Machine Learning Architect with deep exposure to LLMs and agentic AI systems.🔧 Key Responsibilities• Architect and implement LLM-driven and agentic AI solutions for real-world fintech use cases • Stay hands-on across model development, orchestration, evaluation, and deployment • Design scalable ML/AI pipelines with strong MLOps and observability practices • Work closely with product and engineering teams to embed AI into core platform features • Evaluate emerging frameworks, tooling, and models to keep the stack cutting-edge • Mentor engineers and raise the bar for applied AI engineering standards✅ What They’re Looking For• 5+ years in Machine Learning / Applied AI with recent architecture-level ownership • Strong experience working with LLMs, RAG pipelines, and agent orchestration frameworks • Proven ability to take AI solutions from concept to production at scale • Advanced Python skills and familiarity with modern AI tooling (LangChain, LlamaIndex, vector DBs, etc.) • Experience with cloud infrastructure and containerised environments (AWS/GCP/Azure, Docker, Kubernetes) • Background in fintech, trading, or data-intensive products is highly advantageous • A builder mindset — someone who still enjoys coding and shipping Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

First things first: are you customer-obsessed? If the answer is yes, you might be a great fit for Seez.Seez is an AI-powered automotive technology company transforming how vehicles are bought and sold. Since 2016, we've been building scalable SaaS and digital retail solutions that help dealerships, OEMs, and marketplaces deliver smarter, more seamless car buying experiences. Our technology combines AI, data, and automation to power everything from intelligent vehicle discovery to next-generation conversational and generative AI tools.We're looking for a Generative AI & Machine Learning Engineer who thrives at the intersection of research and real-world impact. This role is perfect for someone who loves experimenting with new technologies, solving complex problems, and building intelligent systems that shape the future of automotive retail.Job Key ResponsibilitiesWork closely with business analysts during the requirement definition stage to make sure the business requirements can be implemented in our platformWork day-to-day in a multi-functional team to build and extend machine learning libraries and frameworks to be used in scalable customer facing web applicationsCollaborate with software engineers, product managers, designers, and analystsDeliver testable, maintainable, and high-quality codeMonitor, test, and continuously optimize our Machine Learning modelsEnsure that our user experience is the very best it can beShare knowledge, promote best practices, and collaborate with some of the best Machine Learning engineers in the companyCollaborate with key internal stakeholdersEmploy impeccable analytical and problem-solving abilities to tackle complex challenges in the Machine Learning and AI domainsRegularly update knowledge with the latest trends and developments in the machine learning industryWork effectively with minimal supervision and a proven ability to align data infrastructure with business goalsRequirementsWHAT YOU'LL BRING TO THE PARTY (MUST HAVES)Minimum 2 years work experience. Proven experience with Large Language Models, RAG, fine-tuning, embeddings, and vector databasesExperience with open source LLMs and relevant hardware to host themProficiency with OpenAI API, LangChain ecosystem, and prompt engineering is essentialSkilled in API integration with various providers and enhancing customer experienceDeep familiarity with data structures, data modeling, and software architectureProficiency in Python and SQL. R is considered a plus as wellCompetency in data visualization using R, Python libraries, Tableau, PowerBI, or similar toolsProficiency in using version control tools such as GitStrong ability to understand business needs, data gathering, clear communication, and incorporating feedbackExperience analyzing a feature in production using analytics and experimentsExperience in applying machine learning models to solve real-world problemsYOU'LL THRIVE IN THIS ROLE IF YOU'RE SOMEONE (GREAT-TO-HAVE)Experience working in startupsExperience with cloud services such as AWS and AzureKnowledge of the automotive industry is a plusExperience with writing, releasing, and working in large distributed systems, deep learning or/and natural language processing is a big plusUnderstanding of the fundamentals of machine learning and NLP, with the ability to apply these principles to solve real-world problems, developments in Deep Learning and Language Modeling, especially Generative AI and Large Language ModelsBenefits25 days of paid annual leave plus public holidaysFlexible remote work optionsOpen door policy to CEO and all Leadership teamOne-on-one wellness coaching sessions because your well-being mattersAn annual wellness budget to fuel whatever keeps you balanced—whether that's yoga, hiking, or visit to the museumAn annual learning budget to power your growth—be it a new course, certification, or skill you've been eyeingRegular team events, social calls, the best company SWAG, and a vibrant remote cultureWHY JOIN SEEZ?At Seez, we're all about attracting and keeping top talent, the kind of people who bring ideas, energy, and curiosity to the table. We've created a space where great work gets noticed, collaboration is second nature, and our values aren't just posters on the wall; they guide everything we do.We're a colorful mix of cultures, backgrounds, and perspectives. Everyone has a voice, a purpose, and the freedom to show up as their real self. It's the kind of place where you can do meaningful work, grow quickly, enjoy a healthy work-life balance, and shape your own career path. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

🚀 Machine Learning Architect (LLMs & Agentic AI) | Fintech Startup | Dubai (Hybrid)We’re working with a well-funded fintech startup in Dubai building intelligent, AI-native financial products across trading, automation, and decisioning. As part of their next growth phase, they’re hiring a senior, hands-on Machine Learning Architect with deep exposure to LLMs and agentic AI systems.🔧 Key Responsibilities• Architect and implement LLM-driven and agentic AI solutions for real-world fintech use cases • Stay hands-on across model development, orchestration, evaluation, and deployment • Design scalable ML/AI pipelines with strong MLOps and observability practices • Work closely with product and engineering teams to embed AI into core platform features • Evaluate emerging frameworks, tooling, and models to keep the stack cutting-edge • Mentor engineers and raise the bar for applied AI engineering standards✅ What They’re Looking For• 5+ years in Machine Learning / Applied AI with recent architecture-level ownership • Strong experience working with LLMs, RAG pipelines, and agent orchestration frameworks • Proven ability to take AI solutions from concept to production at scale • Advanced Python skills and familiarity with modern AI tooling (LangChain, LlamaIndex, vector DBs, etc.) • Experience with cloud infrastructure and containerised environments (AWS/GCP/Azure, Docker, Kubernetes) • Background in fintech, trading, or data-intensive products is highly advantageous • A builder mindset — someone who still enjoys coding and shipping Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

First things first: are you customer-obsessed? If the answer is yes, you might be a great fit for Seez.Seez is an AI-powered automotive technology company transforming how vehicles are bought and sold. Since 2016, we've been building scalable SaaS and digital retail solutions that help dealerships, OEMs, and marketplaces deliver smarter, more seamless car buying experiences. Our technology combines AI, data, and automation to power everything from intelligent vehicle discovery to next-generation conversational and generative AI tools.We're looking for a Generative AI & Machine Learning Engineer who thrives at the intersection of research and real-world impact. This role is perfect for someone who loves experimenting with new technologies, solving complex problems, and building intelligent systems that shape the future of automotive retail.Job Key ResponsibilitiesWork closely with business analysts during the requirement definition stage to make sure the business requirements can be implemented in our platformWork day-to-day in a multi-functional team to build and extend machine learning libraries and frameworks to be used in scalable customer facing web applicationsCollaborate with software engineers, product managers, designers, and analystsDeliver testable, maintainable, and high-quality codeMonitor, test, and continuously optimize our Machine Learning modelsEnsure that our user experience is the very best it can beShare knowledge, promote best practices, and collaborate with some of the best Machine Learning engineers in the companyCollaborate with key internal stakeholdersEmploy impeccable analytical and problem-solving abilities to tackle complex challenges in the Machine Learning and AI domainsRegularly update knowledge with the latest trends and developments in the machine learning industryWork effectively with minimal supervision and a proven ability to align data infrastructure with business goalsRequirementsWHAT YOU'LL BRING TO THE PARTY (MUST HAVES)Minimum 2 years work experience. Proven experience with Large Language Models, RAG, fine-tuning, embeddings, and vector databasesExperience with open source LLMs and relevant hardware to host themProficiency with OpenAI API, LangChain ecosystem, and prompt engineering is essentialSkilled in API integration with various providers and enhancing customer experienceDeep familiarity with data structures, data modeling, and software architectureProficiency in Python and SQL. R is considered a plus as wellCompetency in data visualization using R, Python libraries, Tableau, PowerBI, or similar toolsProficiency in using version control tools such as GitStrong ability to understand business needs, data gathering, clear communication, and incorporating feedbackExperience analyzing a feature in production using analytics and experimentsExperience in applying machine learning models to solve real-world problemsYOU'LL THRIVE IN THIS ROLE IF YOU'RE SOMEONE (GREAT-TO-HAVE)Experience working in startupsExperience with cloud services such as AWS and AzureKnowledge of the automotive industry is a plusExperience with writing, releasing, and working in large distributed systems, deep learning or/and natural language processing is a big plusUnderstanding of the fundamentals of machine learning and NLP, with the ability to apply these principles to solve real-world problems, developments in Deep Learning and Language Modeling, especially Generative AI and Large Language ModelsBenefits25 days of paid annual leave plus public holidaysFlexible remote work optionsOpen door policy to CEO and all Leadership teamOne-on-one wellness coaching sessions because your well-being mattersAn annual wellness budget to fuel whatever keeps you balanced—whether that's yoga, hiking, or visit to the museumAn annual learning budget to power your growth—be it a new course, certification, or skill you've been eyeingRegular team events, social calls, the best company SWAG, and a vibrant remote cultureWHY JOIN SEEZ?At Seez, we're all about attracting and keeping top talent, the kind of people who bring ideas, energy, and curiosity to the table. We've created a space where great work gets noticed, collaboration is second nature, and our values aren't just posters on the wall; they guide everything we do.We're a colorful mix of cultures, backgrounds, and perspectives. Everyone has a voice, a purpose, and the freedom to show up as their real self. It's the kind of place where you can do meaningful work, grow quickly, enjoy a healthy work-life balance, and shape your own career path. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

AI / ML EngineerDubai, UAE$220k-$250k + EquityWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 40+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

First things first: are you customer-obsessed? If the answer is yes, you might be a great fit for Seez.Seez is an AI-powered automotive technology company transforming how vehicles are bought and sold. Since 2016, we've been building scalable SaaS and digital retail solutions that help dealerships, OEMs, and marketplaces deliver smarter, more seamless car buying experiences. Our technology combines AI, data, and automation to power everything from intelligent vehicle discovery to next-generation conversational and generative AI tools.We're looking for a Generative AI & Machine Learning Engineer who thrives at the intersection of research and real-world impact. This role is perfect for someone who loves experimenting with new technologies, solving complex problems, and building intelligent systems that shape the future of automotive retail.Job Key ResponsibilitiesWork closely with business analysts during the requirement definition stage to make sure the business requirements can be implemented in our platformWork day-to-day in a multi-functional team to build and extend machine learning libraries and frameworks to be used in scalable customer facing web applicationsCollaborate with software engineers, product managers, designers, and analystsDeliver testable, maintainable, and high-quality codeMonitor, test, and continuously optimize our Machine Learning modelsEnsure that our user experience is the very best it can beShare knowledge, promote best practices, and collaborate with some of the best Machine Learning engineers in the companyCollaborate with key internal stakeholdersEmploy impeccable analytical and problem-solving abilities to tackle complex challenges in the Machine Learning and AI domainsRegularly update knowledge with the latest trends and developments in the machine learning industryWork effectively with minimal supervision and a proven ability to align data infrastructure with business goalsRequirementsWHAT YOU'LL BRING TO THE PARTY (MUST HAVES)Minimum 2 years work experience. Proven experience with Large Language Models, RAG, fine-tuning, embeddings, and vector databasesExperience with open source LLMs and relevant hardware to host themProficiency with OpenAI API, LangChain ecosystem, and prompt engineering is essentialSkilled in API integration with various providers and enhancing customer experienceDeep familiarity with data structures, data modeling, and software architectureProficiency in Python and SQL. R is considered a plus as wellCompetency in data visualization using R, Python libraries, Tableau, PowerBI, or similar toolsProficiency in using version control tools such as GitStrong ability to understand business needs, data gathering, clear communication, and incorporating feedbackExperience analyzing a feature in production using analytics and experimentsExperience in applying machine learning models to solve real-world problemsYOU'LL THRIVE IN THIS ROLE IF YOU'RE SOMEONE (GREAT-TO-HAVE)Experience working in startupsExperience with cloud services such as AWS and AzureKnowledge of the automotive industry is a plusExperience with writing, releasing, and working in large distributed systems, deep learning or/and natural language processing is a big plusUnderstanding of the fundamentals of machine learning and NLP, with the ability to apply these principles to solve real-world problems, developments in Deep Learning and Language Modeling, especially Generative AI and Large Language ModelsBenefits25 days of paid annual leave plus public holidaysFlexible remote work optionsOpen door policy to CEO and all Leadership teamOne-on-one wellness coaching sessions because your well-being mattersAn annual wellness budget to fuel whatever keeps you balanced—whether that's yoga, hiking, or visit to the museumAn annual learning budget to power your growth—be it a new course, certification, or skill you've been eyeingRegular team events, social calls, the best company SWAG, and a vibrant remote cultureWHY JOIN SEEZ?At Seez, we're all about attracting and keeping top talent, the kind of people who bring ideas, energy, and curiosity to the table. We've created a space where great work gets noticed, collaboration is second nature, and our values aren't just posters on the wall; they guide everything we do.We're a colorful mix of cultures, backgrounds, and perspectives. Everyone has a voice, a purpose, and the freedom to show up as their real self. It's the kind of place where you can do meaningful work, grow quickly, enjoy a healthy work-life balance, and shape your own career path. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

AI / ML EngineerDubai, UAE$220k-$250k + EquityWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 40+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information. Show more Show less

Job DescriptionAbout UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Senior Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 5+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Masters degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.Job DetailsRole Level: Mid-Level Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://careers.dyson.com Job Function: Engineering Company Industry/Sector: Appliances Electrical and Electronics ManufacturingWhat We OfferAbout The CompanySearching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.ReportDisclaimer: talentmate.com is only a platform to bring jobseekers & employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

First things first: are you customer-obsessed? If the answer is yes, you might be a great fit for Seez.Seez is an AI-powered automotive technology company transforming how vehicles are bought and sold. Since 2016, we've been building scalable SaaS and digital retail solutions that help dealerships, OEMs, and marketplaces deliver smarter, more seamless car buying experiences. Our technology combines AI, data, and automation to power everything from intelligent vehicle discovery to next-generation conversational and generative AI tools.We're looking for a Generative AI & Machine Learning Engineer who thrives at the intersection of research and real-world impact. This role is perfect for someone who loves experimenting with new technologies, solving complex problems, and building intelligent systems that shape the future of automotive retail.Job Key ResponsibilitiesWork closely with business analysts during the requirement definition stage to make sure the business requirements can be implemented in our platformWork day-to-day in a multi-functional team to build and extend machine learning libraries and frameworks to be used in scalable customer facing web applicationsCollaborate with software engineers, product managers, designers, and analystsDeliver testable, maintainable, and high-quality codeMonitor, test, and continuously optimize our Machine Learning modelsEnsure that our user experience is the very best it can beShare knowledge, promote best practices, and collaborate with some of the best Machine Learning engineers in the companyCollaborate with key internal stakeholdersEmploy impeccable analytical and problem-solving abilities to tackle complex challenges in the Machine Learning and AI domainsRegularly update knowledge with the latest trends and developments in the machine learning industryWork effectively with minimal supervision and a proven ability to align data infrastructure with business goalsRequirementsWHAT YOU'LL BRING TO THE PARTY (MUST HAVES)Minimum 2 years work experience. Proven experience with Large Language Models, RAG, fine-tuning, embeddings, and vector databasesExperience with open source LLMs and relevant hardware to host themProficiency with OpenAI API, LangChain ecosystem, and prompt engineering is essentialSkilled in API integration with various providers and enhancing customer experienceDeep familiarity with data structures, data modeling, and software architectureProficiency in Python and SQL. R is considered a plus as wellCompetency in data visualization using R, Python libraries, Tableau, PowerBI, or similar toolsProficiency in using version control tools such as GitStrong ability to understand business needs, data gathering, clear communication, and incorporating feedbackExperience analyzing a feature in production using analytics and experimentsExperience in applying machine learning models to solve real-world problemsYOU'LL THRIVE IN THIS ROLE IF YOU'RE SOMEONE (GREAT-TO-HAVE)Experience working in startupsExperience with cloud services such as AWS and AzureKnowledge of the automotive industry is a plusExperience with writing, releasing, and working in large distributed systems, deep learning or/and natural language processing is a big plusUnderstanding of the fundamentals of machine learning and NLP, with the ability to apply these principles to solve real-world problems, developments in Deep Learning and Language Modeling, especially Generative AI and Large Language ModelsBenefits25 days of paid annual leave plus public holidaysFlexible remote work optionsOpen door policy to CEO and all Leadership teamOne-on-one wellness coaching sessions because your well-being mattersAn annual wellness budget to fuel whatever keeps you balanced—whether that's yoga, hiking, or visit to the museumAn annual learning budget to power your growth—be it a new course, certification, or skill you've been eyeingRegular team events, social calls, the best company SWAG, and a vibrant remote cultureWHY JOIN SEEZ?At Seez, we're all about attracting and keeping top talent, the kind of people who bring ideas, energy, and curiosity to the table. We've created a space where great work gets noticed, collaboration is second nature, and our values aren't just posters on the wall; they guide everything we do.We're a colorful mix of cultures, backgrounds, and perspectives. Everyone has a voice, a purpose, and the freedom to show up as their real self. It's the kind of place where you can do meaningful work, grow quickly, enjoy a healthy work-life balance, and shape your own career path. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About the role We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale. Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

🚀 Machine Learning Architect (LLMs & Agentic AI) | Fintech Startup | Dubai (Hybrid)We’re working with a well-funded fintech startup in Dubai building intelligent, AI-native financial products across trading, automation, and decisioning. As part of their next growth phase, they’re hiring a senior, hands-on Machine Learning Architect with deep exposure to LLMs and agentic AI systems.🔧 Key Responsibilities• Architect and implement LLM-driven and agentic AI solutions for real-world fintech use cases • Stay hands-on across model development, orchestration, evaluation, and deployment • Design scalable ML/AI pipelines with strong MLOps and observability practices • Work closely with product and engineering teams to embed AI into core platform features • Evaluate emerging frameworks, tooling, and models to keep the stack cutting-edge • Mentor engineers and raise the bar for applied AI engineering standards✅ What They’re Looking For• 5+ years in Machine Learning / Applied AI with recent architecture-level ownership • Strong experience working with LLMs, RAG pipelines, and agent orchestration frameworks • Proven ability to take AI solutions from concept to production at scale • Advanced Python skills and familiarity with modern AI tooling (LangChain, LlamaIndex, vector DBs, etc.) • Experience with cloud infrastructure and containerised environments (AWS/GCP/Azure, Docker, Kubernetes) • Background in fintech, trading, or data-intensive products is highly advantageous • A builder mindset — someone who still enjoys coding and shipping Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

About UsAt Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.About The RoleWe are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.Key ResponsibilitiesArchitect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.About youAt least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).Strong background in feature engineering, data analysis, and data visualization—comfortable using tools like Jupyter, Tableau, or Power BI.Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.Bachelor’s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.4+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

AI / ML EngineerDubai, UAE$220k-$250k + EquityWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 40+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

MissionAre you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you!About UsAily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models, and agentic AI to give business leaders clear, actionable insights in real time.Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, NY and now Dubai. Our mission is to democratize AI in business and enable leaders to Lead Boldly , turning complex data into decisions that drive real, measurable impact.We are looking for AI/ML Engineers who are passionate about the power of AI and love building robust AI/ML systems: people who turn models into reliable, scalable products, and ensure our AI solutions are production-ready, efficient and impactful. Your job is to build and scale the AI/ML infrastructure and pipelines that power Aily’s decision intelligence platform.About This Team - AI PlatformThe AI Platform team is the backbone of Aily’s decision intelligence. We design, build, and operate libraries, tools, and the shared AI/ML infrastructure that enables AI & Data teams to empower business-critical decision-making for our enterprise users.Our 3 missions are to enable innovation at scale, to minimize entropy, and to accelerate progress for Aily.If you enjoy working at the intersection of AI and software, closely collaborating & empowering other teams, setting technical direction, and turning complexity into leverage, this team is the right place to make your mark.Your profileCore responsibilities (by seniority)Mid AI/ML Engineer - 3+ years of experiencePartner with Data Scientists and Engineers to bring AI solutions to productionDesign and implement end-to-end ML pipelines (data→model→deployment→monitoring) autonomouslyContribute to APIs, tools, and libraries used by more than 100 AI team members daily (including Cloud & LLM Infrastructure and AI-driven features)Communicate with your team: present results and findings, identify gaps and opportunities, and learn to explain our product and software/AI behindRequirements: Solid AI/ML fundamentals, strong Python, APIs/K8s/Docker/Cloud experience, mentor junior team members on technical topicsSenior AI/ML Engineer - 4+ years of experienceAll of the above +Own complex projects, lead technical initiatives from design to implementation (refactoring, standardization)Ensure the quality of your own and your teams' developmentsInteract with other functions and agree on exchange protocols and architecture design (DevOps, Front End, Data Engineering, Back End, …)Sponsor the creation and implementation of new software and ML standards in the AI teamRequirements: Strong software engineering practices, Deep AI/ML knowledge, outstanding problem-solving skills, ability and willingness to lead and mentor Junior team membersPrincipal AI/ML Engineer - 6+ years of experienceAll of the above +Shape AI Platform strategy across teams and be a technical reference for Aily’s AI teamLead cross-team design sessions, define, enforce, and maintain org-wide standards"Make things happen" at scale, manage leadership pressureLead a team of 4+ AI/ML Engineers and own their roadmapRequirements: Driven by impact and value, able to lead multiple technical initiatives in parallel, mastery in the modern AI/ML stack (AWS, FastAPI, Docker, K8s, Python, CI/CD, Airflow, Agentic coding, concurrency, etc)Who we’re looking for (all levels)You are impact-driven and thrive at the intersection of AI, business, ML engineering, and product. You want to build real systems that power decision-making at scale.A builder: you enjoy shipping reliable solutions, improving systems and tooling, and making things work in production at scale.A strong collaborator who enjoys working with Data Scientists, Product Managers, and Engineers, and can explain trade-offs and designs in simple terms.Someone with a startup mindset: comfortable with ambiguity, proactive, hands-on, and willing to improve things beyond your immediate scope.Ready to Lead Boldly - helping Aily and its customers scale AI systems that enable faster, smarter decisions every day.Applicants must already have the legal right to work in SpainLocation & detailsLocations: DubaiContract type: PermanentAbout UsLEARN MORE Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Experience Required (Number of Years): 10-15 YearsDescription Skill/Experience/QualificationAnalyze large datasets to identify trends, patterns, and actionable insights.Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.Collaborate with stakeholders to define business problems and translate them into data science solutions.Communicate findings through visualizations, dashboards, and presentations.Stay up to date with the latest data science techniques and tools.Experience with cloud platforms (AWS, Azure)Familiarity with big data technologies (Spark, Hadoop).Knowledge of MLOps and model deployment best practices.Strong understanding of statistical methods and data modeling. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.Designing and implementing effective and impactful machine learning systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of work, our tooling, and our internal training programs.QualificationsTechnical ExperienceExperience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow)QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.6+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

Job SummaryWe are seeking an experienced AI / ML Business Analyst to support enterprise AI initiatives by translating business problems into AI/ML use cases, defining success metrics, and ensuring measurable business value. The role acts as the business anchor for AI products, working closely with AI Engineers, Product Owners, and stakeholders—without requiring hands-on technical or coding expertise. Key Responsibilities1) AI Use Case Discovery & Framing• Identify and define AI / ML use cases aligned to business strategy.• Translate business challenges into AI-ready problem statements.• Define objectives, assumptions, constraints, and expected outcomes.2) Requirements for AI & ML Solutions• Gather and document:o Business requirementso Functional AI requirements (inputs, outputs, decisions, automation scope)o Non-functional requirements (accuracy targets, explainability, compliance, SLAs)• Create AI-specific BRDs, user stories, and acceptance criteria.• Ensure requirements are feasible, measurable, and aligned to AI delivery timelines.3) KPI, Value & ROI Definition• Define KPIs for AI solutions (accuracy, automation %, time saved, cost reduction).• Build business value and ROI models for AI initiatives.• Track post-deployment benefits realization.4) Stakeholder & AI Team Collaboration• Act as the primary business interface for:o AI Engineerso Data Science teamso Product Owners• Facilitate workshops on AI feasibility, scope, and prioritization.• Ensure business expectations are aligned with AI system capabilities.5) Governance, Risk & Responsible AI Support• Support AI governance processes (approvals, documentation, audits).• Identify business risks related to AI adoption, bias, explainability, and compliance.• Ensure alignment with Responsible AI principles from a business perspective. Core Competencies• Strong experience working on AI / ML or analytics-driven initiatives• Business requirements management for data-driven systems• KPI definition and value realization• Excellent stakeholder communication and facilitation skills Preferred Qualifications• Experience in real estate / construction AI use cases• Exposure to AI concepts such as:o ML models, RAG, AI agents (conceptual understanding)• Certifications (nice-to-have):o Lean Six Sigmao Agile Business Analysis What Success Looks Like• Clearly defined AI use cases with measurable outcomes• Strong alignment between business goals and AI delivery• High adoption and value realization of AI solutions• Reduced scope creep through strong AI-specific requirements Show more Show less

Job DescriptionKey Responsibilities Independently design and implement end-to-end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization. Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi-step tasks using APIs, tools, enterprise systems, and external services. Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool-using agents. Hands-on model selection, fine-tuning, evaluation, and optimization for LLMs, transformer-based architectures, diffusion models, and other advanced AI models. Design advanced system components such as agent memory, reflection loops, vector stores, and long-horizon planning mechanisms to support scalable agentic intelligence. Work closely with cross-functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs. Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems. Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems. Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization. Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives. Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands-on ownership of core development activities. Education and Qualification Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate 8-10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems. Proven track record in architecting large-scale AI platforms, integrating LLMs, and designing multi-agent systems. Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face Transformers). Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies. Hands-on experience with agentic frameworks (e.g., LangChain Agents, AutoGPT, OpenAgents, CrewAI) and orchestration of autonomous agents. Deep knowledge of planning, reasoning, and decision-making architectures for autonomous systems. Experience in cloud-native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry. Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments. Familiarity with reinforcement learning, symbolic reasoning, and neuro-symbolic AI approaches. Experience with real-time data processing, event-driven architectures, and MLOps best practices for production-grade AI systems. Show more Show less

AI / ML EngineerDubai, UAE$220k-$250k + EquityWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 40+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information. Show more Show less

Job PurposeTo lead and implement AI/ML initiatives across the Bank’s technology landscape, aligning strategic objectives with data-driven insights, while ensuring regulatory compliance, operational efficiency, and innovation through the use of machine learning and advanced analytics.Minimum Qualification: Master’s Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.ExperienceMinimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role.Proven experience in banking or financial services is highly preferred.Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark).Experience in Azure ML tools: Databricks etc.Experience with end-to-end model lifecycle management and MLOps. Show more Show less

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.In this role, you will: Query large datasets with SQL and feed ML models Perform data exploration to find patterns in the data and understand the state and quality of the data available Utilize Python code for analyzing data and building statistical models to solve specific business problems Evaluate ML models and fine tune model parameters considering the business problem behind Collaborate with senior peers to Deploy ML models in production Build customer-facing reporting tools to provide insights and metrics which track system performance Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data Participate in the off-hours on call stability rotation to support live ML models Requirements Bachelor's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field Statistical modelling and math Basic knowledge of Machine learning algorithms Basic knowledge of SQL Basic knowledge of visualization tools such as Periscope Excellent verbal and written communication Strong problem solving skills BenefitsAbility to contribute to a platform used by more than 5M users in UAE and other platforms in the regionStrengthen your resume and build your networkOpportunity to find a full time career with the region's leading organizationWorking in a multicultural environment with over 60 different nationalitiesAccess to the Learning & Development tools and courses provided by the companyBayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.#UAEdubizzle Show more Show less

Transguard Workforce Solutions is the UAE’s leading provider of unique and innovative HR solutions. With a decade of experience in the region and a team that possesses extensive knowledge of the market, we provide a fully integrated HR solution.We are currently recruiting for an Data Scientist - Machine Learning for our client to be based out of their Dubai office.Job PurposeThe role is responsible for designing, developing, and productionizing AI/ML models that deliver measurable business impact. It owns the full lifecycle from framing business problems and shaping datasets to model training, deployment with MLOps best practices, and postlaunch monitoring. The role ensures models are accurate, reliable, and aligned with business objectives, while translating complex business requirements into actionable AI solutions and promoting transparency across key processes and performance indicators.Responsibilities• Design, train, validate, and deploy advanced ML/DL models (NLP, CV, transformers, statistical learning). • Optimize models for accuracy, scalability, and latency to ensure production readiness. • Apply Responsible AI principles, including fairness, bias detection, and explainability.• Build and manage pipelines, feature stores, and ingestion frameworks (real-time and batch). • Implement MLOps practices: CI/CD workflows, registries, automated retraining, and observability. • Monitor and resolve issues related to data drift, leakage, and model reliability• Ensure compliance with GDPR, ISO standards, ICAO digital/AI frameworks, and organizational policies. • Promote transparency of AI-driven KPIs and processes across the enterprise. • Conduct fairness audits, model explainability, and ethical risk assessments. • Translate complex, ambiguous business challenges into AI/ML opportunities. • Define scope, feasibility, and expected value of AI initiatives. • Advise stakeholders on risks, trade-offs, and adoption strategies.Professional Certification Requirements: Professional certification in Machine Learning (preferred)Relevant Experience (Years): 5-6 YearsSkills, Tools, and Systems Experience:• Programming & Data Science: Python, R, SQL, StreamLit • ML & AI Frameworks: TensorFlow, PyTorch, Keras, scikit-learn, Hugging Face • MLOps & Deployment: Docker, Kubernetes, Git CI/CD • Data Engineering: Apache Spark, Kafka, dbt • Cloud Platforms: Azure ML • Visualization: Power BI, Tableau • Responsible AI Tools: AI Governance Platform (e.g. Atlan) Show more Show less

Position: Senior Machine Learning EngineerLocation: Dubai (onsite)Employment Type: Full-timeExperience Level: Senior level ⸻ About the ClientOur client is a Dubai-based gaming software development company focused on creating immersive, high-quality video and mobile gaming experiences. Combining creative design with advanced engineering, the company develops interactive games and digital entertainment products for a global audience. With a strong emphasis on innovation, user engagement, and scalable technology, the firm continues to expand its portfolio across platforms while contributing to the growing gaming and interactive media ecosystem in the region. About the RoleThis senior-level Machine Learning Engineer position is dedicated to advancing artificial intelligence and machine learning solutions within the gaming software development industry. The role focuses on designing, developing, and deploying sophisticated ML models and algorithms that enhance gameplay, personalize user experiences, and optimize in-game systems. As a senior contributor, this position plays a pivotal role in shaping the AI strategy, mentoring junior engineers, and driving innovation in a fast-paced, creative environment.Key ResponsibilitiesArchitect, design, and implement advanced machine learning models tailored to gaming applications, including player behavior prediction, procedural content generation, and real-time decision-making systems.Lead the end-to-end lifecycle of AI/ML projects, from data collection and preprocessing to model training, evaluation, deployment, and monitoring in production environments.Collaborate closely with game designers, software engineers, and data scientists to integrate ML solutions seamlessly into game engines and live gaming platforms.Develop and optimize algorithms for real-time inference, ensuring low-latency and high-performance AI features within interactive gaming experiences.Conduct rigorous experimentation and A/B testing to validate model effectiveness and drive continuous improvement of in-game AI systems.Ensure the scalability, reliability, and maintainability of ML pipelines and infrastructure, leveraging cloud-based and on-premises resources as appropriate.Mentor and provide technical guidance to junior ML engineers and data scientists, fostering a culture of knowledge sharing and best practices.Stay abreast of the latest advancements in AI, deep learning, and gaming technologies, proactively introducing innovative techniques and tools to the team.Document model architectures, data flows, and technical decisions to support transparency and future development.Collaborate with cross-functional teams to ensure compliance with ethical AI standards and data privacy regulations relevant to the gaming industry.Required Experience & SkillsExtensive experience (typically 5+ years) in designing, developing, and deploying machine learning and deep learning models in production environments, with a strong portfolio of projects in gaming or related interactive domains.Advanced proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Keras, with demonstrated ability to implement custom neural network architectures.Deep understanding of supervised, unsupervised, and reinforcement learning techniques, with practical experience applying these methods to real-world problems.Strong background in data engineering, including data preprocessing, feature engineering, and handling large-scale, complex datasets relevant to gaming analytics.Proven expertise in deploying ML models for real-time inference, optimizing for performance and scalability in latency-sensitive environments.Experience with cloud platforms (e.g., AWS, GCP, Azure) and ML infrastructure tools such as Docker, Kubernetes, and MLflow for model management and deployment.Solid grasp of software engineering best practices, including version control (Git), code reviews, testing, and CI/CD pipelines.Excellent problem-solving skills, with the ability to translate ambiguous business or gameplay requirements into concrete ML solutions.Strong communication and collaboration skills, with experience working in multidisciplinary teams and mentoring junior staff.Familiarity with ethical AI considerations, data privacy, and responsible AI practices in the context of gaming and user data.QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field; a PhD is advantageous.Demonstrated track record of delivering impactful AI/ML solutions in the gaming industry or similar high-interactivity environments.Publications, open-source contributions, or patents in AI/ML or gaming technology are considered a plus.Participation in relevant industry conferences, competitions, or communities is desirable.Tools & TechnologiesProgramming Languages: Python (primary), C++ or C# (for game engine integration)ML/DL Frameworks: TensorFlow, PyTorch, Keras, Scikit-learnData Processing: Pandas, NumPy, Apache SparkGame Engines: Unity, Unreal Engine (for AI integration)Cloud Platforms: AWS, Google Cloud Platform, Microsoft AzureContainerization & Orchestration: Docker, KubernetesModel Management: MLflow, TensorBoardVersion Control: GitExperiment Tracking: Weights & Biases, Neptune.aiVisualization: Matplotlib, Seaborn, Plotly This position offers the opportunity to drive the next generation of AI-powered gaming experiences, directly influencing gameplay, personalization, and player engagement. The role provides a platform for technical leadership, creative problem-solving, and career growth within a dynamic and innovative industry at the intersection of artificial intelligence and interactive entertainment. By applying to this position, you are granting us permission to process your CV and keep your profile on file for consideration for this and future opportunities. Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.4+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

AI / ML EngineerDubai, UAE$220k-$250k + EquityWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 40+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information. Show more Show less

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.NVIDIA is looking for a Professional Services Engineer to join its infrastructure Specialist team. Academic and commercial groups around the world are using NVIDIA Runai platform to improve productivity and efficiency for data scientists. Our product provides a unique HPC scheduler, relies on advanced GPUs virtualization technology and Provides an easy access to GPU based environments for data scientist and ML engineers. Join the team building many of the largest and fastest AI/HPC systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic, customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners, and internal teams to analyze, define, and implement large-scale AI/HPC projects.What You Will Be DoingHelp our customers with the installation and onboarding of the Run:ai softwareOn a daily basis to maximize to help increase the value of the Run.AI software. These includes:Helping data scientists and ML engineers embed best practices in the world of machine learning operations.Configuring Run:ai to match customer’s use caseIntegrate run:ai into customer's existing ML ops environment including scriptingDiagnosing and solving customer issues in sophisticated cloud native environmentsUse existing profiling and analysis tools to find bottlenecks and low utilization of deep learning models.Collaborates with internal stakeholders (e.g. Pre-Sales Solution Engineers, Account Managers, Account SAs, Product) in the post-sale stage by understanding business requirements and providing industry and technical input.Develop new tools and scripts to help simplify integration between Run:ai to other Data Science tools.What We Need To See3+ years of experience working in a customer facing role at a B2B SaaS/On Prem Software CompanyB.Sc in Computer Science or equivalent experienceExperience presenting to technical audiences and creating technical content for developersExperience in Linux / Unix Operating SystemsHands on experience with KubernetesExperience in containerization technologies like Docker, containersProven experience with software developmentWays To Stand Out From The CrowdCKANVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous manager who loves a challenge? Are you ready to become the staff member you always wanted to be? Come and be part of the best SW design team in the industry!NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all., , JR2012853 Show more Show less

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation. Many of our initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations.ResponsibilitiesLeveraging ambiguous business problems as opportunities to drive objective criteria using data.Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.Designing and implementing effective and impactful machine learning and generative AI systems in production.Developing a deep understanding of the product experiences and business processes that make up your area of focus.Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.Working closely with product and business teams to identify important questions that can be answered effectively with data.Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.Designing, planning, and analyzing experiments (A/B and multivariate tests).Supporting product and business managers with KPI design and goal setting.Mentoring other data scientists in their growth journeys.Contributing to improving our ways of working, our tooling, and our internal training programs.QualificationsRequirementsTechnical ExperienceExperience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).Excellent SQL.Competence with reproducible data analysis using Python or R.Familiarity with data modeling and dimensional design.Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.4+ years of experience working in data science, machine learning, and Gen AI.Experience doing data science in an online consumer product setting is a plus.A good problem solver with a ‘figure it out’ growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A ‘keep it simple’ approach to #makeithappen. Show more Show less

Position: Senior Machine Learning EngineerLocation: Dubai (onsite)Employment Type: Full-timeExperience Level: Senior level ⸻ About the ClientOur client is a Dubai-based gaming software development company focused on creating immersive, high-quality video and mobile gaming experiences. Combining creative design with advanced engineering, the company develops interactive games and digital entertainment products for a global audience. With a strong emphasis on innovation, user engagement, and scalable technology, the firm continues to expand its portfolio across platforms while contributing to the growing gaming and interactive media ecosystem in the region. About the RoleThis senior-level Machine Learning Engineer position is dedicated to advancing artificial intelligence and machine learning solutions within the gaming software development industry. The role focuses on designing, developing, and deploying sophisticated ML models and algorithms that enhance gameplay, personalize user experiences, and optimize in-game systems. As a senior contributor, this position plays a pivotal role in shaping the AI strategy, mentoring junior engineers, and driving innovation in a fast-paced, creative environment.Key ResponsibilitiesArchitect, design, and implement advanced machine learning models tailored to gaming applications, including player behavior prediction, procedural content generation, and real-time decision-making systems.Lead the end-to-end lifecycle of AI/ML projects, from data collection and preprocessing to model training, evaluation, deployment, and monitoring in production environments.Collaborate closely with game designers, software engineers, and data scientists to integrate ML solutions seamlessly into game engines and live gaming platforms.Develop and optimize algorithms for real-time inference, ensuring low-latency and high-performance AI features within interactive gaming experiences.Conduct rigorous experimentation and A/B testing to validate model effectiveness and drive continuous improvement of in-game AI systems.Ensure the scalability, reliability, and maintainability of ML pipelines and infrastructure, leveraging cloud-based and on-premises resources as appropriate.Mentor and provide technical guidance to junior ML engineers and data scientists, fostering a culture of knowledge sharing and best practices.Stay abreast of the latest advancements in AI, deep learning, and gaming technologies, proactively introducing innovative techniques and tools to the team.Document model architectures, data flows, and technical decisions to support transparency and future development.Collaborate with cross-functional teams to ensure compliance with ethical AI standards and data privacy regulations relevant to the gaming industry.Required Experience & SkillsExtensive experience (typically 5+ years) in designing, developing, and deploying machine learning and deep learning models in production environments, with a strong portfolio of projects in gaming or related interactive domains.Advanced proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Keras, with demonstrated ability to implement custom neural network architectures.Deep understanding of supervised, unsupervised, and reinforcement learning techniques, with practical experience applying these methods to real-world problems.Strong background in data engineering, including data preprocessing, feature engineering, and handling large-scale, complex datasets relevant to gaming analytics.Proven expertise in deploying ML models for real-time inference, optimizing for performance and scalability in latency-sensitive environments.Experience with cloud platforms (e.g., AWS, GCP, Azure) and ML infrastructure tools such as Docker, Kubernetes, and MLflow for model management and deployment.Solid grasp of software engineering best practices, including version control (Git), code reviews, testing, and CI/CD pipelines.Excellent problem-solving skills, with the ability to translate ambiguous business or gameplay requirements into concrete ML solutions.Strong communication and collaboration skills, with experience working in multidisciplinary teams and mentoring junior staff.Familiarity with ethical AI considerations, data privacy, and responsible AI practices in the context of gaming and user data.QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field; a PhD is advantageous.Demonstrated track record of delivering impactful AI/ML solutions in the gaming industry or similar high-interactivity environments.Publications, open-source contributions, or patents in AI/ML or gaming technology are considered a plus.Participation in relevant industry conferences, competitions, or communities is desirable.Tools & TechnologiesProgramming Languages: Python (primary), C++ or C# (for game engine integration)ML/DL Frameworks: TensorFlow, PyTorch, Keras, Scikit-learnData Processing: Pandas, NumPy, Apache SparkGame Engines: Unity, Unreal Engine (for AI integration)Cloud Platforms: AWS, Google Cloud Platform, Microsoft AzureContainerization & Orchestration: Docker, KubernetesModel Management: MLflow, TensorBoardVersion Control: GitExperiment Tracking: Weights & Biases, Neptune.aiVisualization: Matplotlib, Seaborn, Plotly This position offers the opportunity to drive the next generation of AI-powered gaming experiences, directly influencing gameplay, personalization, and player engagement. The role provides a platform for technical leadership, creative problem-solving, and career growth within a dynamic and innovative industry at the intersection of artificial intelligence and interactive entertainment. By applying to this position, you are granting us permission to process your CV and keep your profile on file for consideration for this and future opportunities. Show more Show less