AI Jobs in Dubai

We Are Hiring | AI Specialist (AI, Automation & Digital Transformation)Work Location: Dubai Investment Park (DIP) 2, Dubai, UAEWe are looking for a Full Stack Developer with strong AI, automation, functional, and technical knowledge to build and support our in-house software and digital transformation initiatives.The role will focus on understanding business processes, identifying manual work, developing software solutions, integrating departmental workflows, implementing AI, and continuously improving business operations.Key ResponsibilitiesDevelop and maintain in-house business applications.Understand departmental workflows and convert manual and Excel-based processes into software automation.Work with Joinery, MEP, Manufacturing, Projects, Procurement, Finance, HR, and other departments to identify automation opportunities.Develop AI-powered solutions for production planning, scheduling, reporting, estimation, material planning, quality analysis, and workflow optimization.Build dashboards, reports, and management information systems to support decision-making.Develop an in-house AI chatbot to help employees access information, interact with internal systems, and support business processes.Develop an internal task and work management system similar to Jira to assign, track, prioritize, monitor, and report departmental tasks and projects.Develop AI-assisted workflows for SOPs, documentation, reports, and operational records.Design and develop solutions with a clean, well-structured, and scalable architecture, always considering scalability, performance, efficiency, maintainability, and future business growth. Work directly with Department Heads, stakeholders, and the Assistant General Manager to understand business requirements.Implement AI, automation, APIs, and emerging technologies to improve business processes.Support employees in adopting AI tools and provide AI training and guidance where required.Continuously evaluate emerging technologies and implement solutions that provide measurable business value.Take ownership of development from requirement gathering, design, development, testing, deployment, and support.Server-related activities will be handled by the Headquarters IT & Intelligence Team. Ensure fast and efficient development and implementation, without compromising clean architecture, scalability, maintainability, or overall solution quality.Mandatory Technical Skills.NET / C#PythonSQLReact / Next.jsREST APIs & API IntegrationAI / LLM / AI API IntegrationRequirementsMinimum 2+ years of Full Stack Software Development experience.Strong Functional and Technical knowledge.Ability to understand business processes and independently develop practical software solutions.Strong interest in AI, automation, and emerging technologies.Ability to work with changing requirements and develop flexible solutions.Strong analytical and problem-solving skills.Ability to work independently while collaborating with the Headquarters IT & Intelligence Team.Willingness to learn, experiment, and introduce new technology ideas to the organization.This is an opportunity for someone who wants to go beyond traditional software development and contribute to building an integrated in-house technology ecosystem connecting business processes, people, tasks, data, and AI across the organization.

About the Role Explore data, engineer features, and build machine learning models for real business challenges. Design, run, and evaluate experiments to support products such as fraud detection, recommendation engines, ranking, and personalisation. Collaborate closely with ML engineers and backend developers to bring successful models into production. Present insights and findings to both technical and non-technical stakeholders. Contribute to a collaborative, data-driven environment focused on continuous learning and innovation.Requirements 0–2 years of experience in Data Science (internships, research projects, and academic work are welcomed). Strong Python skills with experience using pandas, NumPy, and scikit-learn. Solid understanding of machine learning, statistics, and experimental design. Good SQL skills. Strong analytical thinking and communication skills. Nice to have: Exposure to Spark, Databricks, recommendation systems, fraud detection, or SaaS/high-scale product environments.Benefits Competitive salary with annual performance bonus. Comprehensive medical insurance. Annual flight allowance. Visa sponsorship. Annual leave entitlement. Learning and conference budget to support your professional growth. Hybrid working model with flexibility. Opportunity to work alongside experienced engineers and data scientists on cutting-edge AI/ML products with a distributed team across Dubai and Europe.

AI Strategy and Vision Develop a comprehensive AI and data science strategy that aligns with the company's objectives and long-term vision. Identify and evaluate opportunities for integrating AI and data science into existing processes and operations to improve efficiency and decision making. Lead end-to-end project management of AI initiatives, from conception to deployment and post-implementation evaluation. Collaborate with cross-functional teams to define project scope, requirements, and deliverables. Data Analysis and Modeling Oversee the development of machine learning models and algorithms for various applications, such as predictive analytics, natural language processing, and computer visionEnsure data quality and integrity and implement best practices for data preprocessing and feature engineering and model evaluationEvaluate and select appropriate tools, technologies and frameworks for data analysis and modelingEstablish monitoring mechanisms to track project performance, identify areas for improvement, and report progress to stakeholdersCreate repeatable, interpretable, dynamic, and scalable models seamlessly incorporated into analytic data productsInnovation and Research Stay abreast of the latest developments and trends in AI and data science, exploring innovative solutions and emerging technologies that can benefit the organizationRegularly evaluate the performance of AI projects and data science initiatives and provide detailed reports to senior managementUse data-driven insights to propose improvements and optimizations to existing processesData PrivacyEnsure compliance with data privacy regulations and ethical guidelines throughout all data science activitiesImplement data protection measures and maintain confidentiality of sensitive informationIdentify potential risks and challenges associated with AI projects and data science initiatives RequirementsBachelor's or Master's Degree in Computer Sciences / Data Science/ AIStrong background in machine learning, statistical analysis, and data visualization

We offer flexibility in location for this role, enabling you to support our international customer base and contribute to our continued growth.At Datafusion.AI, we are revolutionizing voice and data capturing and processing for telecommunications and governmental agencies through innovative IP and Voice data stream processing and analytics. Our cutting-edge solutions shape the future of global communication, processing billions of data points daily and directly impacting government operations.We are seeking a talented and exceptional Artificial Intelligence/Machine Learning Engineer who wants to make a difference in the world, has a strong drive for continuous learning and development, is open and collaborative, and never stops striving to improve themselves and the products or services they are responsible for. You will be responsible for developing and optimizing advanced machine learning (ML) models across various domains, including natural language processing (NLP), computer vision, and speech processing. This role requires broad expertise in large language modelsKey ResponsibilitiesDesign, implement, and fine-tune Large Language Models (LLMs) for various NLP tasks, including text classification, entity extraction, sentiment analysis, and conversational AI applications.Develop and optimize diffusion models for generating synthetic data, augmenting data, and creating multimodal content to enhance training datasets.Build and maintain end-to-end machine learning pipelines for text processing, speech recognition, and multimodal data analysis.Implement state-of-the-art transformer architectures and attention mechanisms for various sequence modeling tasks across different data modalities.Research and integrate cutting-edge ML techniques, including few-shot learning, transfer learning, and multi-task learning approaches.Collaborate with engineering teams to deploy ML models in production environments, ensuring scalability and reliability.Develop custom training strategies, loss functions, and evaluation frameworks for domain-specific applications in telecommunications and government sectors.Optimize model performance, inference speed, and resource utilization for deployment across various hardware configurations.Conduct comprehensive model evaluation, A/B testing, and performance monitoring to ensure continuous improvement.Create technical documentation, research reports, and best practice guidelines for ML development processes.Mentor junior team members and contribute to the advancement of ML practices across the organization.Required QualificationsAdvanced degree in Computer Science, Machine Learning, Data Science, Mathematics, or a related field.4+ years of experience in machine learning engineering with a focus on deep learning and neural networks.Strong proficiency in Python and extensive experience with PyTorch, TensorFlow, and the HuggingFace ecosystem.Demonstrated expertise with Large Language Models including GPT, BERT, T5, LLaMA, and similar transformer-based architectures.Hands-on experience with diffusion models such as Stable Diffusion, DDPM, DDIM, or similar generative modeling techniques.Experience with ASR (Automatic Speech Recognition) systems and speech processing pipelines, including models like Whisper, Wav2Vec2, or similar technologies.Solid understanding of natural language processing techniques, including tokenization, embeddings, attention mechanisms, and sequence modeling.Experience with parameter-efficient fine-tuning methods, including LoRA, QLoRA, AdaLoRA, and other PEFT techniques.Knowledge of distributed training, model parallelism, and large-scale data processing frameworks.Familiarity with MLOps practices, model deployment, and production monitoring systems.Strong mathematical foundation in statistics, linear algebra, and optimization theory.Technical SkillsProgramming Languages: Expert-level Python; proficiency in C/C++, JavaScript, or Julia for performance optimization.Deep Learning Frameworks: Advanced experience with PyTorch, TensorFlow, JAX, and HuggingFace Transformers.LLM Technologies: Extensive knowledge of transformer architectures, attention mechanisms, tokenizers, and model scaling techniques.Generative Models: Hands-on experience with diffusion models, VAEs, GANs, and other generative modeling approaches.Fine-Tuning Techniques: Proficiency with LoRA, QLoRA, prefix tuning, prompt tuning, adapters, and instruction tuning methodologies.NLP Libraries: Experience with spaCy, NLTK, Gensim, sentence-transformers, and domain-specific NLP tools.Speech Processing: Familiarity with librosa, torchaudio, SpeechBrain, and audio processing pipelines.Model Optimization: Knowledge of quantization, pruning, distillation, ONNX, TensorRT, and inference optimization.Data Processing: Expertise in pandas, NumPy, Apache Spark, Dask, and distributed computing frameworks.MLOps Tools: Experience with Docker, Kubernetes, MLflow, Weights & Biases, Ray, and cloud ML platforms.Proficient in version control using Git, DVC, and collaborative ML development workflows.Preferred QualificationsExperience with multimodal learning combining text, audio, and visual data modalities.Knowledge of reinforcement learning from human feedback (RLHF) and constitutional AI approaches.Familiarity with federated learning and privacy-preserving machine learning techniques.Experience with real-time inference systems and streaming data processing.Understanding of model interpretability, explainable AI, and bias detection methodologies.Knowledge of graph neural networks and knowledge graph embedding techniques.Experience with AutoML frameworks and neural architecture search (NAS).Contributions to open-source ML projects or published research in top-tier conferences.Experience with edge deployment and mobile optimization for ML models.Understanding of cybersecurity applications and adversarial machine learning.Personal AttributesExceptional problem-solving skills and ability to approach complex ML challenges from first principles.Strong research mindset with the ability to stay current with the rapidly evolving ML/AI landscape.Excellent communication skills, both written and verbal, with the ability to explain complex concepts to diverse audiences.Self-driven and proactive, with a passion for pushing the boundaries of machine learning technology.Adaptable and open-minded, able to work effectively across different problem domains and data modalities.Collaborative team player with experience working in cross-functional environments.Strong attention to detail with commitment to reproducible and ethical AI practices.Additional InformationLanguage: Fluent oral and written English is mandatory.Good interpersonal skillsExcellent organizational skillsTeam player but able to work on own initiativeGood written and oral communication skillsEnthusiastic, self-starter and highly self-motivatedAppreciation of cultural differencesAttention to detailTravel: Occasional travel may be required for conferences, client meetings, or inter-office collaboration.We offer a very competitive package with excellent benefits and the opportunity to work on cutting-edgetechnologies that shape the future of telecommunications and data analytics. If you are a visionary technologist passionate about advancing the state-of-the-art in machine learning and making a global impact through innovative AI solutions, we want to hear from you!

I’m partnering with a fast-growing fintech to hire a Lead AI Engineer for a highly technical, hands-on leadership role.This isn’t a typical “AI Engineer” position. We’re looking for someone whose foundations are genuinely in AI/ML, data science and research — someone who understands the mathematics behind the models, can read cutting-edge research and turn it into working software, but who has also developed the engineering breadth to build and ship complete products.A PhD / significant academic research background in AI, Machine Learning, Computer Science or a closely related discipline is essential for this search.What you’ll be doingLead forward-looking AI/ML research and development from 0 → 1Build, train, validate and calibrate ML models — not simply integrate model APIsTurn new research papers and emerging techniques into working prototypes and production systemsWork across foundation models, agents, causal inference, real-time ML and streaming analyticsTake ideas from research through to production across models, data infrastructure, backend services and product interfacesSet the technical and architectural direction for ambitious AI initiativesRemain highly hands-on — coding, experimenting and prototypingHelp build and mentor a high-performing AI/engineering teamWhat we’re looking forPhD / strong research background — essentialDeep foundations in Machine Learning / Data Science / AI8+ years’ experience across AI, ML and engineering with evidence of having built and shipped real ML modelsStrong Python and modern ML frameworks such as PyTorch / TensorFlowExperience with distributed data technologies such as Spark, Kafka, Snowflake or DatabricksAbility to understand and implement ideas from academic AI/ML researchStrong engineering capability across production-grade systemsExperience taking AI/ML research from experimentation into scalable productsStrong product mindset — you care about how what you build is actually usedComfortable operating as a senior individual contributor, not simply managing from a distancePublished research, open-source AI contributions and experience within fintech would be particularly interesting.This is a rare opportunity for someone who wants to sit at the intersection of AI research, machine learning, engineering and product, with genuine ownership over what gets built.If your career started closer to models and research and expanded into engineering — rather than the other way around — I’d particularly like to hear from you.

AI Software EngineerLocation: Hybrid(UAE)Type: Full-TimeAbout the RoleWe are working with an innovative technology company looking for an AI Software Engineer to join a high-performing engineering team building next-generation AI-powered applications.This is an opportunity to work on complex LLM-based systems, designing intelligent workflows and developing production-ready AI solutions that solve challenging real-world problems. You'll collaborate with software engineers, product teams and domain experts to build scalable, reliable AI capabilities while staying at the forefront of emerging technologies.ResponsibilitiesDesign, build and enhance production-grade LLM-powered applications.Develop prompt architectures and agentic AI workflows.Build evaluation frameworks and define meaningful metrics to measure model performance and reliability.Design and implement scalable software solutions using Python and modern engineering best practices.Integrate AI capabilities into existing platforms, services and backend systems.Prototype, test and productionise new AI features and model interactions.Improve quality, safety and observability through monitoring, testing and guardrails.Collaborate closely with cross-functional teams to deliver high-quality technical solutions.Contribute to architecture discussions and share knowledge with the wider engineering team.Required Skills & ExperienceCommercial experience building complex LLM-based applications.Strong prompt engineering skills with experience designing agentic AI workflows.Experience creating evaluation frameworks, benchmarks and custom performance metrics for AI systems.Strong software engineering fundamentals with excellent Python development experience.Experience building scalable production systems.Familiarity with cloud platforms, CI/CD pipelines and modern software engineering practices.Passion for keeping up to date with the latest AI research and emerging technologies.Excellent problem-solving and communication skills.Comfortable working in a fast-paced, collaborative engineering environment.Desirable ExperienceExperience working on production AI platforms.Understanding of model monitoring, evaluation and observability.Knowledge of software architecture and distributed systems.Experience collaborating across engineering, product and technical teams.What's on OfferFully remote working across the UAE.Competitive salary and benefits package.Flexible working hours.Annual learning and development budget.Home office equipment allowance.Opportunity to work on cutting-edge AI technology.Collaborative, high-performing engineering culture.Long-term career growth within an innovative technology business.

Who we are GIG Gulf is part of the Gulf Insurance Group (GIG), the #1 largest regional composite insurer in the Middle East and North Africa, with presence in 13 markets including the United Arab Emirates, Bahrain, Oman, Qatar, Saudi Arabia, Algeria, Egypt, Iraq, Jordan, Kuwait, Lebanon, and Turkey. GIG Group reported consolidated assets of US$ 3.83 billion and $69 million net profit for the year 2023. The majority shareholder of GIG Group is Toronto based Fairfax Financia Holding, a global leader in insurance and reinsurance with a presence in 40 markets.GIG Gulf is an ‘A’ rated regional insurer with a top 5 position in each of its markets (UAE, Oman, Qatar, Bahrain). GIG Gulf has been present in the region for over 70 years with a strategic focus on both growth and investments and is a one stop shop offering a wide range of insurance products and services that cater to a broad variety of needs for corporates, SMEs and individual customers throughout UAE, Oman, Bahrain, and Qatar. GIG Gulf also owns a 50% stake in GIG Saudi. Our strategic objectives and guiding principles are focused on Regional Growth, Customer Experience and Digital Transformation.GIG Gulf has created a diverse and inclusive working environment and culture with a workforce of over 800 employees, with over 60 nationalities, across 15 branches and retail shops region-wide and over 1 million customers. GIG Gulf is a caring partner that encourages customers to achieve their goals and live an inspiring and fulfilling life. We are obsessed with customer feedback and continuously evolving to become the region’s digital insurer of reference, committed to running our operations in a responsible, sustainable way.Job purpose:Are you passionate about turning Artificial Intelligence from experimentation into measurable business value?As an AI Engineer, you will play a hands-on role in designing, building, deploying, and operating enterprise-grade AI solutions that support GIG Gulf's AI Adoption agenda. You will work closely with technology teams, data professionals, security teams, and external partners to create AI-enabled products, intelligent automation capabilities, GenAI solutions, AI agents, and decision-support systems that are secure, scalable, compliant, and production-ready.The role supports bridging the gap between AI innovation and business outcomes by developing solutions that improve customer experience, operational efficiency, employee productivity, risk management, and decision-making across the organizationAs a AI Engineer, you will work closely with business and IT stakeholders to:develop and evolve business AI solutions lead pilots, POCs and exploration of new innovative solutions, practices and patternsdesign and deliver cloud‑based and AI‑enabled solutions that are secure, scalable, and fit for purposeactively contribute to the organization’s AI delivery priorities, ensuring alignment with business outcomes, regulatory requirements, and operational realitiesKey Responsibilities:In collaboration with GIG Gulf business and IT stakeholders and considering information system landscape, business ambitions, recommendation, best practices, technology evolution and market trends:AI EnablementWork with architecture, data, and business teams to translate business problems into AI-enabled solutions.Assist in evaluating emerging AI technologies, frameworks, platforms, and vendor offerings.Promote reuse of enterprise AI capabilities, patterns, and shared services.AI Solution EngineeringDesign and develop AI, GenAI, and Agentic AI solutions.Build intelligent applications leveraging LLMs, SLMs, AI Agents, RAG architectures, and enterprise AI platforms.Develop AI-enabled workflows, copilots, chatbots, search experiences, document intelligence solutions, and automation use cases.Create reusable AI components, accelerators, and development standards.Implement retrieval architectures using vector databases, embedding models, and knowledge repositories.Ensure AI solutions leverage approved and governed enterprise data sources.Collaborate with Data Architecture and Integration teams to establish scalable AI foundations.AI Operations (LLMOps / MLOps)Deploy AI workloads using enterprise cloud platforms including Azure and AWS. Establish automated DevOps processes. Monitor model performance and support lifecycle management, versioning, evaluation, and continuous improvement. Governance, Security & Responsible AIEnsure compliance with enterprise AI governance frameworks and policies.Embed security, auditability and accountability controls into AI solutions.Implement safeguards against prompt injections, data leakage, model abuse and adversarial attacks.Innovation & Continuous ImprovementLead pilots, proofs of concept, and experimentation initiatives for emerging AI technologies.Assess new AI capabilities and provide recommendations based on business value and risk.Contribute to development of AI engineering standards, frameworks, and reusable assets.Stay current on advancements in GenAI, Agentic AI, LLMs, foundation models, AI infrastructure, and industry trends.Operational & Technical Responsibilities:AI EngineeringFunction as an active hands-on AI Engineer for enterprise and business initiatives:Develop AI solutions using Python, low code application development and modern AI frameworks.Build and optimize prompts, workflows, orchestration layers, and agent behaviors.Develop solutions leveraging approved AI services (e.g. OpenAI, Azure AI, AWS AI, Anthropic, Google).Implement semantic search, retrieval augmentation, knowledge grounding, and contextual reasoning solutions.Generative AI & Agentic AI SolutionsDesign and implement enterprise-grade GenAI solutions including:Retrieval Augmented Generation (RAG)AI copilots and assistantsMulti-agent workflowsEnterprise knowledge searchIntelligent document processingAutomation and decision-support systemsHuman-in-the-loop AI workflowsQuality, Testing & EvaluationStructured testing of AI outputs, hallucination management, and response quality controls.Continuously improve model performance and user experience.Knowledge Management & DocumentationMaintain technical documentation, architecture diagrams, model cards, and operational procedures.Business / Domain knowledge requirements (desirable)Understanding of regulatory considerations affecting AI deployment in financial services and insurance. Familiarity with data privacy, residency, and compliance requirements within UAE and GCC markets. Basic knowledge of the insurance businessRole Requirements:Bachelor of Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Systems, or related discipline.Microsoft Azure AI Engineer AssociateAWS Certified Machine Learning Engineer / Specialty3-5 years of experience in software engineering, cloud engineering, machine learning, Automation or AI.1 - 2 years of hands-on experience implementing AI or ML solutions.Experience building and deploying cloud-native applications or automations.Demonstrated experience delivering business-focused technology solutions.AI EngineeringAbility to design, develop, deploy, monitor, and operate production-grade AI solutions.Python Development and automationAbility to build scalable AI applications and integrations.Generative AIExperience with:LLM such as Anthropic Claude, OpenAI, Google Gemini, Azure OpenAIAgent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, AWS Agentcore, Google ADK, Microsoft Agent FrameworkRAG and retrieval: vector databases (such as Pinecone, pgvector, Qdrant), semantic search and embeddingsWorkflow orchestration, automation and/or other intelligent automation toolingPrompt EngineeringCloud Engineering and hands-on experience using Azure and/or AWS for AI workloads, cross-cloud deployment, IaC (such as Terraform, Pulumi), CI/CD pipelinesAI EngineeringAbility to design, develop, deploy, monitor, and operate production-grade AI solutions.Python Development and automationAbility to build scalable AI applications and integrations.Generative AIExperience with:LLM such as Anthropic Claude, OpenAI, Google Gemini, Azure OpenAIAgent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, AWS Agentcore, Google ADK, Microsoft Agent FrameworkRAG and retrieval: vector databases (such as Pinecone, pgvector, Qdrant), semantic search and embeddingsWorkflow orchestration, automation and/or other intelligent automation toolingPrompt EngineeringCloud Engineering and hands-on experience using Azure and/or AWS for AI workloads, cross-cloud deployment, IaC (such as Terraform, Pulumi), CI/CD pipelinesCollaborationGood stakeholder management skills across business, IT, and control functionsAbility to communicate technical topics clearly Comfortable working in a high‑demand, delivery‑oriented environmentCommunication and Soft SkillsExcellent communication skills in English, both verbal and writtenTeam player – ability to work with a team and influence a positive collaborative culture Ability to prioritize workload appropriately based on the impact on the businessDemonstrated ability to work independently while efficiently managing multiple projects simultaneously.

About the RoleWe're looking for an AI Engineer who can take ideas from prototype to production — building scalable AI/ML systems and the data architecture behind them. This is a hands-on role combining strong software engineering, applied machine learning, Generative AI and data engineering.The ideal candidate will be responsible for developing practical AI solutions that support business transformation, automation and improved decision-making across AGMC.What You'll DoDesign, build and optimize ML/DL models and LLM-powered applications, including Agentic AI, Generative AI and RAG solutions.Build end-to-end AI pipelines covering training, inference, evaluation and monitoring.Develop clean, scalable and well-tested backend services and APIs using FastAPI / Flask.Design data architecture and manage data storage, primarily using PostgreSQL, including schema design, data modelling and performance optimization.Work with large datasets, including data preprocessing, feature engineering and model evaluation.Develop and integrate AI solutions into existing business applications and systems.Monitor AI/ML models in production and continuously improve accuracy, latency, reliability and scalability.Develop proof-of-concepts and take successful AI solutions through to production.Collaborate with IT, Digital, Product, Data and business teams to identify and deliver AI use cases.Ensure AI solutions follow appropriate security, privacy, governance and responsible AI practices.Stay up to date with emerging AI technologies and identify opportunities to apply them within AGMC.What We're Looking ForStrong Python skills and solid software engineering fundamentals, including clean code, testing and Git.Hands-on experience with PyTorch and/or TensorFlow.Practical experience with Agentic AI, Generative AI, LLMs and RAG.Experience with LLM frameworks and tooling such as LangChain and/or LlamaIndex.Strong data architecture and database skills, particularly PostgreSQL.Familiarity with vector databases such as Pinecone, Weaviate or FAISS.Experience with cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform.Understanding of MLOps and production deployment, including Docker, Kubernetes, CI/CD and MLflow.Experience developing and consuming REST APIs.Strong analytical and problem-solving skills.Clear communicator with the ability to work independently and take ownership of projects from concept through to production.Experience working in an Agile / collaborative environment.Nice to HaveBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering or a related field.Maximum 2 years experience deploying AI applications at scale within an enterprise environment.Strong prompt engineering skills and understanding of AI safety and responsible AI.Experience with AI agents and multi-agent architectures.Exposure to reinforcement learning or multimodal AI.Experience working with automotive, retail, mobility or other customer-focused industries would be an advantage.Experience taking AI solutions from proof-of-concept to production.Tools & TechnologiesPython · FastAPI / Flask · PyTorch / TensorFlow · PostgreSQL · SQL · LangChain / LlamaIndex · RAG · Vector Databases · Docker · Kubernetes · Git · AWS · Azure · GCP · MLflow · CI/CD

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 Sr. Data Scientist (AI & ML) on the global AI hub, your mission will be to design, build, and ship the machine learning and generative AI systems that power decisions across product and business. You will own a particular domain end to end, working closely with product and business managers as part of a talented team of data scientists and machine learning engineers. You will own the full ML lifecycle, from problem framing, data modeling, and feature engineering through model training, deployment, serving, and monitoring in production. Many of our initiatives will focus on leveraging Generative AI and LLMs for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations at scale.ResponsibilitiesFraming ambiguous business problems as well-defined machine learning and data science problems, with clear, objective success criteria.Providing high-quality, impactful insights and data-driven recommendations through rigorous analysis and automated reporting to drive strategic organizational choices.Designing, building, and shipping end-to-end machine learning and generative AI systems in production — spanning data pipelines, feature engineering, model training, serving, and monitoring.Taking on engineering-heavy work end to end: architecting robust ML-based systems, writing clean and scalable production code, and training, deploying, and maintaining reliable ML models that solve real business problems at scale.Training, evaluating, and iterating on models — selecting the simplest, most appropriate algorithms and architectures to deliver measurable business value.Leveraging LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making within production systems.Building and maintaining the data models, features, and pipelines that power model training and allow us to measure performance and its drivers for your area of focus.Designing, planning, and analyzing experiments (A/B and multivariate tests) to rigorously measure model and product impact.Developing deep familiarity with source data and its generating systems through documentation, collaboration with engineering teams, and systematic data profiling.Partnering with product and business teams to identify high-impact opportunities and translate them into ML solutions and actionable, data-driven recommendations.Mentoring other data scientists in their growth journeys.Elevating engineering and ML best practices — improving our ways of working, tooling, MLOps, and internal training programs.QualificationsTechnical ExperienceDeep expertise in machine learning, generative AI, deep learning, recommendation systems, NLP, pattern recognition, data mining.Deep hands-on knowledge of ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Transformers, LLM fine-tuning).Strong software engineering fundamentals: excellent coding skills, a solid grasp of data structures and algorithms, and proven ability in both general system design and ML system design.Proven experience building, deploying, serving, and monitoring ML models in production, with a strong grasp of MLOps practices.Strong data and ML engineering skills, including building and orchestrating data and training pipelines (e.g. via Airflow) and robust feature engineering.Excellent SQL and competence with reproducible analysis and modeling in Python.Solid statistical foundations, including experiment design and analysis (A/B and multivariate) and inferential, causal, and predictive methods.Familiarity with data modeling and dimensional design.Strong command over the entire ML lifecycle, from problem formulation and data auditing through modeling, deployment, interpretation, and presentation.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.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.5+ years of experience across data science, machine learning engineering, and generative AI, including shipping ML models to production.Experience building ML systems 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.

We are currently seeking a AI Engineer who will be responsible for designing, building, integrating, and operationalizing enterprise-grade AI solutions across the organization. The role will focus on practical AI engineering using Microsoft Copilot, Copilot Studio with the underlying models from OpenAI, Anthropic, and modern Generative AI capabilities to improve business processes, knowledge access, productivity, and digital service delivery.You will work closely with business stakeholders, IT delivery teams, data owners, and vendors to translate business needs into secure, scalable, and maintainable AI-enabled solutions. The ideal candidate combines strong technical AI development experience with sound business understanding, clear communication skills, and the ability to deliver AI solutions responsibly within an enterprise environment.Our client based in Dubai, is one of the largest semi-governmental conglomerates in the region. This position is a contract role with an initial duration of 12 months and is renewable.Key Responsibilities:Design, develop, test, and deploy AI-enabled solutions using Copilot, Copilot Studio, LLM APIs, orchestration frameworks, and enterprise integration patterns.Build practical GenAI use cases such as conversational assistants, knowledge retrieval experiences, workflow copilots, document intelligence, summarization, and productivity automation.Develop prototypes and production-ready AI components that integrate with enterprise systems, data sources, APIs, and Microsoft 365 services.Configure and extend Microsoft 365 Copilot, Copilot Studio agents, custom copilots, topics, actions, connectors, prompts, and enterprise knowledge grounding patterns.Work with OpenAI / ChatGPT and Claude models, including effective prompt design, model selection, response evaluation, guardrails, context handling, and performance optimization.Apply Retrieval-Augmented Generation (RAG), embeddings, vector search, function calling, tool use, and agentic workflow concepts where appropriate.Collaborate Techno-Functional developers to define AI solution designs, integration approaches, APIs, data flows, authentication, and security boundaries.Connect AI solutions to structured and unstructured enterprise data sources while considering data quality, permissions, sensitivity, and governance requirements.Produce technical documentation including architecture notes, integration specifications, prompt libraries, model evaluation notes, and operational runbooks.Embed responsible AI principles, privacy, compliance, security, and risk considerations into AI solution design and delivery from the start.Support model and prompt evaluation, hallucination control, access control validation, data leakage prevention, and safe-use guidance for business users.Contribute to AI governance artefacts, standards, reusable patterns, and technical controls for enterprise AI adoption.Work with business stakeholders to understand pain points, assess AI feasibility, refine requirements, and translate business needs into technical AI solutions.Support discovery workshops, solution demos, user testing, adoption activities, and continuous improvement cycles for AI-enabled products and services.Balance technical feasibility, business value, user experience, delivery effort, and operational sustainability when shaping AI use cases.Apply software engineering practices including version control, code review, testing, environment management, deployment discipline, and ongoing monitoring.Evaluate AI outputs using defined quality criteria, feedback loops, test datasets, prompt regression checks, and business acceptance measures.Stay current with developments across Copilot, OpenAI, Claude, Azure AI, GenAI frameworks, and emerging enterprise AI patterns.Knowledge, Skills & Experience:5+ years of technology delivery or software engineering experience, with meaningful hands-on exposure to AI, automation, data, or enterprise application development.Hands-on experience with Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry / Azure Open AI, or comparable enterprise AI platforms.Practical experience designing or developing AI-enabled solutions using LLMs, APIs, prompt engineering, workflow automation, or intelligent assistants.Experience with OpenAI / ChatGPT, Claude, embeddings, vector databases, RAG architectures, LangChain / Semantic Kernel, or agentic AI frameworks.Strong understanding of Generative AI concepts, model behaviour, prompting techniques, grounding, evaluation, limitations, and responsible AI considerations.Experience integrating AI solutions with Microsoft 365, SharePoint, Teams, Power Platform, Dynamics 365, Salesforce, ERP, ITSM, or other enterprise systems.Ability to translate business requirements into technical designs, prototypes, production-ready AI features, and measurable business outcomes.Knowledge of data governance, privacy, security, access control, content classification, and enterprise compliance requirements.Working knowledge of APIs, JSON, authentication concepts, secure integration patterns, data handling, and software development lifecycle practices.Experience in real estate, leasing, asset management, customer experience, or other business domains relevant to enterprise operations.Strong analytical, troubleshooting, communication, and documentation skills, with the ability to explain technical AI concepts to non-technical stakeholders.Cloud, AI, Agile, or software engineering certifications such as Microsoft AI / Azure certifications, Scrum, SAFe, or equivalent credentials.Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related field.Consulting, product delivery, or client-facing experience delivering AI, automation, or digital transformation solutions.

About noonnoon, the region's leading consumer commerce platform. On December 12th, 2017, noonlaunched its consumer platform in Saudi Arabia and the UAE, expanding to Egypt in February2019. The noon ecosystem of services now marketplaces for food delivery, quick commerce,fintech, and fashion. noon is a work in progress; we’re six years in, but only 5% done.noon’s mission: Ring every doorbell, every day.Who are we?Everyday Labs is noon’s innovation engine — a place built to imagine, build, and scale new ideas that create real value for users, for noon, and for the world. Our mission is simple: turn imagination into measurable impact. We explore new technologies, test new business models, and launch products that push noon’s ecosystem forward with speed, clarity, and purpose.If you want to build models, ML pipelines and AI that become the foundation for future noon businesses, this is where you belong.About the role:As a Staff Machine Learning Engineer at Everyday Labs, you will architect and deliver the intelligence that powers our next generation of products, experiments, and ventures. You will work at the intersection of applied machine learning, experimentation, and scalable engineering — building models and ML infrastructure that can go from idea to deployed value with exceptional velocity and rigor.This is a highly technical, high-ownership role where you will influence technical strategy, hire and mentor engineers, and help shape the culture and systems that allow ML ideas to become high-impact reality.What you'll do:Machine Learning: Turning Ideas into Value • Design, train, and deploy ML models that deliver measurable impact across multiple aspects of noon’s vast e-commerce footprint.• Translate ambiguous or zero-to-one problems into clear hypotheses, measurable signals, and verifiable ML solutions.• Collaboration with product, engineering and business leaders to define value metrics and success thresholds early and rigorously.Production ML Systems & Pipelines:• Architect reliable training, validation, and deployment pipelines using modern MLOps practices.• Build and maintain feature stores, automated retraining systems, online inference services, and monitoring frameworks.• Ensure systems meet high bars for observability, reliability, and performance — excellence in execution is part of our signature.Technical Leadership & Cross-Team Ownership:• Hire and mentor ML and software engineers across Labs in traditional ML, generative AI technologies.• Contribute to cross-initiative architecture, documentation, and open knowledge sharing.• Work noon partners and stakeholders to apply ML where it can unlock disproportionate impact.What you'll need:• 6+ years of experience in applied ML engineering• Bachelor's degree in Computer Science, Engineering, or a related technical field, master’s or PhD is a plus but not required.• Strong proficiency with Python, modern ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost), and model lifecycle best practices.• Proven experience deploying ML models into real-world systems with CI/CD and automated monitoring.• Strong SQL and data engineering fundamentals, including building scalable data pipelines (Airflow or similar).• Experience with cloud platforms (AWS, GCP, Azure). GCP is a plus.• Experience with generative AI, LLMs, or NLP systems is a strong bonus.

Position: Senior AI Engineer Compensation: Competitive salary plus family benefits & variable Location: Dubai, United Arab Emirates OverviewGateworth Group is partnering with a technology organisation in the UAE that is scaling its AI engineering function and building a specialist team focused on high‑performance model optimisation. They’re investing heavily in advanced AI infrastructure and are seeking senior engineers who can work deep inside modern LLMs, improve inference behaviour, and shape how large‑scale models run in production.This role suits someone who enjoys complex, hands‑on engineering, understands how transformer architectures behave at scale, and can move confidently between model internals, systems performance, and deployment‑level optimisation. You’ll work across analysis, tuning, benchmarking and architectural decision‑making, contributing to next‑generation AI systems.Main Responsibilities• Improve and optimise LLM inference performance across distributed, multi‑chip and multi‑node environments• Apply strong understanding of transformer architectures, including dense and Mixture‑of‑Experts (MoE) models• Benchmark leading LLMs (LLaMA, Mistral, Qwen, DeepSeek) across varied hardware stacks• Design and implement attention‑level optimisations (Flash Attention, grouped‑query, sliding‑window)• Deliver model‑level optimisation including quantisation (INT8/FP8), KV‑cache strategies, batching and parallelism• Work closely with hardware, systems and compiler teams to co‑design efficient inference pipelines• Build and maintain benchmarking frameworks to measure latency, throughput and scaling behaviour• Evaluate architectural trade‑offs and contribute to deployment strategies for large‑scale environments• Stay current with research across LLM architectures, inference optimisation and performance engineeringQualifications• Strong understanding of transformer architectures, LLM internals and both dense/MoE models• Hands‑on experience with modern LLMs (LLaMA, Mistral, Qwen, DeepSeek) and attention‑level optimisation• Practical experience with inference optimisation: quantisation (INT8/FP8), KV‑cache strategies, batching, pruning and parallelism• Strong Python skills with PyTorch or JAX, plus experience profiling and debugging performance bottlenecks• Background in distributed systems, large‑scale inference workloads and system‑level optimisation across hardware and runtime layers• Ideally 8+ years in deep learning, AI systems or performance engineering, with exposure to datacenter‑scale inference (e.g., vLLM) and hardware‑aware optimisationApplyCandidates who meet the above criteria and are seeking a progressive, technically challenging role are invited to apply via the link provided. For further questions, contact apply@gateworth.com quoting reference #8341.

About the jobEstablished in 2004, Dubai Holding is a global investment company with investments in more than 34 countries and a combined workforce of nearly 45,000 individuals. In line with the vision of Dubai’s leadership and economic diversification strategy, Dubai Holding companies have nurtured sectors, irrevocably transforming Dubai’s socio-economic landscape and positioning Dubai as a diversified, globally integrated economy.Dubai Holding is committed to the diversification of Dubai’s non-oil economy. Our portfolio, valued at over AED 284+ billion, spans 10 sectors, including real estate, hospitality, leisure & entertainment, ICT, design, education, media, retail, manufacturing & logistics, and science.For the Good of TomorrowDubai Holding is looking to hire a Manager AI Software Engineering at the corporate office, reporting to the Associate Director Software Engineering. The job holder is responsible for designing, building, deploying, and operating production-grade AI agents on Microsoft Foundry – LLM-powered systems that reason, use tools, and orchestrate multi-step workflows against enterprise data and services. This is a hands-on, pro-code role: the engineer writes Python, integrates Azure services, and ships agentic applications that drive measurable business impact. The engineer works within agile teams alongside Product, Data Science, and Architecture to take agent use-cases from prototype to production, ensuring solutions are reliable, performant, and continuously improved.The role is responsible for technical delivery of AI solutions and does not own product priorities, which are defined by Product Managers.Key Responsibilities:AI Solution Design & Development Design, build, and iterate AI agents using Microsoft Foundry, leveraging its agent framework, model catalogue, and tool/function-calling capabilitiesImplement AI solutions in Python, incorporating LLM application patterns such as RAG, tool use, structured outputs, memory, and multi-agent orchestrationIntegrate AI agents with Palantir Foundry via MCP (Model Context Protocol) to access enterprise data and execute ontology-driven actionsTranslate product requirements into scalable technical designs aligned to defined use casesDeployment & Productionisation Deploy AI agent solutions into production environments using CI/CD pipelines, including automated evaluations as release gatesManage versioning of code, prompts, tools, and agent configurations to ensure controlled and repeatable releasesConfigure and optimize agent architectures, prompts, and tooling to meet performance, cost, and latency targetsEnsure solutions are production-ready, scalable, and aligned to enterprise delivery standardsOperation & Service ReliabilityOperate AI agents in production, including observability, tracing, cost monitoring, regression testing, and incident responseMonitor system performance and reliability, addressing issues related to latency, cost efficiency, and output qualityMaintain secure handling of enterprise data, including authentication, authorization, and secret management using Azure services (Key Vault, Entra ID)Platform Integration & EngineeringIntegrate AI applications with Azure services including Azure OpenAI, AI Search, Storage, Functions, Container Apps, and identity servicesBuild and maintain scalable architecture patterns for agent-based applications across cloud platformsContribute to reusable components, shared libraries, and standardized engineering practices across squadsEvaluation & Continuous Improvement Build and maintain evaluation harnesses and guardrails covering groundedness, safety, latency, and costAnalyze system performance and iterate on prompts, tools, and architectures based on measured outcomesContinuously improve AI solutions based on user feedback, production data, and delivery insightsCross-Functional DeliveryWork within agile product squads alongside Product Managers, Data Scientists, and Architects to deliver AI use cases from prototype to productionCommunicate technical trade-offs (model selection, latency, cost, accuracy) clearly to technical and non-technical stakeholdersSupport alignment between engineering delivery and product priorities, ensuring timely and effective executionWho we are looking for:2+ years of experience deploying agentic AI systemsSoftware engineering experience with hands-on production experience building LLM-based / agentic systems (tool use, orchestration, RAG, evals)Education / Professional Certifications:Bachelor’s degree in computer science, Engineering, or related quantitative fieldAdvanced degrees preferredTechnical Competencies:Strong Python — idiomatic, typed, tested; comfortable with async and modern packagingProven experience building production AI agents in code (e.g. Microsoft Foundry / Azure AI Foundry, Semantic Kernel, AutoGen, LangGraph, LlamaIndex, OpenAI Agents SDK, or equivalent custom frameworks)Microsoft Foundry experience is strongly preferred (agent authoring, model catalog, connectors, deployment)Azure exposure — Azure OpenAI, AI Search, identity, storage, serverless compute; familiarity with Azure DevOps or GitHub ActionsDeep working knowledge of LLM application patterns: tool/function calling, structured outputs, RAG, memory, multi-agent orchestrationExperience with evaluation frameworks and observability for LLM systems (tracing, prompt/response logging, automated evals)DevOps fundamentals: Git, CI/CD, containers, infrastructure-as-code; exposure to data engineering and vector stores is a plusBehavioral CompetenciesStrong ownership and accountability for delivering high-quality technical solutionsStructured problem-solving and analytical capabilityAbility to collaborate effectively within cross-functional delivery teamsClear communication of technical concepts and trade-offsAdaptability in fast-paced and evolving delivery environmentsAs much as we would be delighted to entertain all applicants, due to the high volumes of applications, only successful applicants will be contacted within 14 business days. This job description is not all inclusive. Dubai Holding reserves the right to amend this job description at any time. Dubai Holding is an Equal Opportunity Employer, committed to a diverse and inclusive work environment.

Data & AI Specialist (Manager Level)We're looking for a Data & AI Specialist to join one of our clients, supporting PR, communications, and business growth through AI-powered analytics, measurement, and automation. This role sits at the intersection of data science, artificial intelligence, media intelligence, and strategic communications, helping teams turn complex data into actionable insights while driving the responsible adoption of AI across the business.Key ResponsibilitiesIntegrate AI into agency workflows and communications processes.Design AI-driven solutions for media analysis, sentiment, audience insights, search visibility, and content performance.Build dashboards, automated workflows, prompts, and lightweight AI tools.Use AI and analytics to support PR measurement, reputation tracking, trend analysis, and strategic decision-making.Partner with strategy, digital, creative, and analytics teams to develop data-driven solutions.Evaluate AI outputs for accuracy, bias, transparency, and effectiveness.Research emerging AI technologies and measurement methodologies.Document processes and ensure insights are clear and trustworthy.RequirementsBachelor's degree in Data Science, Computer Science, Analytics, Statistics, or a related field (or equivalent experience).5+ years' experience in data analytics, AI, machine learning, or business analytics.Strong Python and SQL skills.Experience with Power BI, Tableau, Looker Studio, Excel, or similar BI tools.Hands-on experience with generative AI, large language models, prompt engineering, or NLP.Understanding of PR, media intelligence, social listening, reputation, or digital communications measurement.Ability to translate complex data into clear, actionable business insights.PreferredExperience in PR analytics, media intelligence, communications strategy, or digital marketing analytics.Experience building dashboards, reporting automation, and internal AI tools.Knowledge of AI governance, bias evaluation, and explainable AI.Arabic language skills are an advantage but not required.Ideal CandidateA technically strong, commercially minded professional who enjoys solving business problems with AI and data. You'll be comfortable working across technical and non-technical teams, building practical AI solutions, and helping shape the future of communications through data-driven insight while ensuring human judgement remains at the centre of decision-making.

We are seeking an experienced AI Technical Lead / AI Solution Architect to design and deliver production-grade AI/ML solutions within a government or highly regulated environment.The role combines hands-on AI engineering, solution architecture, Generative AI expertise and technical leadership. The successful candidate will define technical solutions, guide implementation, review architecture and code, and technically lead AI delivery teams.Key RequirementsProven hands-on experience designing and delivering AI/ML solutions into production.Strong practical knowledge of Machine Learning, Generative AI/LLMs and Agentic AI.Strong Python development skills, with the ability to prototype, review and guide production AI/ML implementations.Practical experience with RAG, embeddings, vector search, prompt engineering, tool/function calling, agent orchestration and LLM evaluation.Strong AI solution architecture and integration capabilities, including scalability, security, reliability, performance and cost considerations.Experience designing AI solutions across public cloud, hybrid, private or sovereign cloud environments.Strong Microsoft Azure experience, ideally including Azure OpenAI, Azure AI Foundry, Azure AI Search and Azure Machine Learning.Understanding of MLOps/LLMOps, including deployment, evaluation, monitoring, versioning and production lifecycle management.Strong understanding of AI security, governance, responsible AI, data privacy and data sovereignty.Experience with modern software engineering practices including APIs, microservices, containers, Kubernetes and CI/CD.Proven experience technically leading and mentoring AI Developers, ML Engineers and Data Scientists.Technical StackExperience with relevant technologies across:GenAI/LLM: Azure OpenAI, Azure AI Foundry, OpenAI-compatible APIs, Hugging Face or equivalent.RAG & Search: Azure AI Search, vector databases, embeddings and semantic search.Agentic AI: LangChain, LangGraph, Semantic Kernel, LlamaIndex or equivalent agent frameworks.ML/MLOps: Azure Machine Learning, MLflow or equivalent.Cloud & Engineering: Microsoft Azure, REST APIs, microservices, Docker, Kubernetes, Git and CI/CD.Data: SQL/NoSQL, data pipelines, data lakes/lakehouses; Databricks, Spark or Microsoft Fabric are advantageous.Depth of technical capability is more important than experience with every named technology.Preferred ExperienceGovernment or highly regulated environments.Experience with data residency, sovereignty, security and regulatory requirements.AI governance, cybersecurity and responsible AI.Production MLOps / LLMOps.Computer Vision.High-volume, scalable or real-time AI solutions.Open-source or self-hosted LLMs.Hybrid, private or sovereign cloud architectures.

Forward Deployed EngineerWe are looking for a Forward Deployed Engineer to join our Team and work directly with operating companies across the Group to turn real-world operational challenges into deployed AI solutions.This is a hands-on engineering role for someone who enjoys working closely with business users, understanding how work is performed, building practical AI solutions and taking them all the way from discovery to production and handover.The successful candidate will combine software engineering, AI/LLM development, systems integration and business problem-solving to deliver solutions that create measurable operational value.Key ResponsibilitiesWork directly with operating companies to identify operational problems and translate them into practical AI and automation solutions.Conduct process discovery, requirements gathering and stakeholder interviews.Design, build, test and deploy AI-powered solutions using internal platforms, models and reusable components.Develop solutions using Python, LLM APIs, RAG, vector databases, agent frameworks and workflow orchestration.Integrate AI solutions with existing operational systems, APIs, data sources and business workflows.Rapidly prototype solutions, test them with real users and iterate towards production-ready implementations.Develop evaluation and testing frameworks to measure AI solution quality and performance.Monitor deployed solutions in production and troubleshoot performance, quality and integration issues.Work with Group IT, Information Security, Data & Analytics and business teams to ensure appropriate architecture, security and compliance.Document solutions and prepare technical handover materials.Train business users and operational owners to use, maintain and extend deployed solutions.Track and report measurable benefits from each deployment, including cost savings, productivity improvements and licence displacement.Identify reusable components and patterns that can accelerate future AI deployments across the Group.Support build-versus-buy assessments by demonstrating the technical feasibility and total cost of internally developed solutions.Where required, lead temporary delivery pods or coordinate the work of interns.RequirementsBachelor's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, Industrial Engineering or a related discipline.1–3 years of hands-on experience building and deploying software or AI solutions into production.Proven experience delivering solutions used by real users beyond proof-of-concept or experimental environments.Recent practical experience developing applications using Large Language Models (LLMs) is required.Strong experience with Python for application development and/or data-related work.Experience working with LLM APIs, prompt engineering and context design.Practical knowledge of Retrieval-Augmented Generation (RAG) and vector databases.Experience with AI agent frameworks and workflow orchestration.Experience with APIs, system integration, SQL and data pipelines.Exposure to AI evaluation and testing frameworks.Experience with cloud platforms and deploying/managing applications in cloud environments.Exposure to lightweight front-end development for internal tools is an advantage.Strong process mapping, business analysis and requirements-gathering skills.Ability to communicate technical concepts to non-technical stakeholders.Experience working directly with clients, business units or operational teams is strongly preferred.Exposure to logistics, supply chain or operations-heavy environments is an advantage.Key Technical SkillsPython | Generative AI | LLMs | LLM APIs | Prompt Engineering | RAG | Vector Databases | AI Agents | Workflow Orchestration | API Integration | SQL | Data Pipelines | AI Evaluation | Cloud Deployment | Software Development | Process AutomationWhat We Are Looking ForWe are looking for an engineer who is comfortable operating at the intersection of technology and business.You should be able to take an ambiguous operational problem, understand it directly from users, design a technical solution, build it, deploy it into production and ensure that the business can successfully use and maintain it.Candidates whose experience is limited to academic projects, training or POCs without production deployment experience will not be considered.

Lead AI Engineer (AI/ML Engineering)Location: Dubai, UAE (Onsite)We are hiring a Lead AI Engineer to join a major enterprise organization building a next generation AI capability. This is a highly hands on engineering role focused on designing, building, and deploying production grade AI applications at enterprise scale.This is not a research or AI consulting role. We are looking for engineers who can take AI solutions from concept to production.Key ResponsibilitiesDesign, develop, and deploy production AI applicationsBuild scalable backend services, APIs, and AI workflowsDevelop LLM, RAG, and Agentic AI solutionsIntegrate AI capabilities into enterprise platformsDesign production ready data pipelines and microservicesEnsure scalability, reliability, security, and performanceCollaborate with cross functional teams to deliver enterprise AI solutionsMandatory SkillsStrong Python developmentFastAPI, Flask, or DjangoBackend API development and MicroservicesLLMs, RAG, LangChain, LangGraph, Agentic AISQL/PostgreSQLDocker & KubernetesAWS, Azure, or GCPProduction AI/ML deployment experienceCI/CD, MLOps, or LLMOpsExperience building end to end AI applicationsPreferred BackgroundSoftware Engineering / Computer Science / Data ScienceStrong backend engineering foundationExperience in Logistics, Retail, FMCG, FinTech, Banking, or large enterprise environmentsExperience owning AI products from POC to Production

Data Science ConsultantI am looking for someone to join a growing consulting team delivering bespoke AI and analytics solutions that help organisations solve complex commercial challenges through data. This is a client-facing role combining data science, consulting and technical delivery, where you'll work closely with business stakeholders to translate requirements into scalable analytical solutions.You will design and deliver end-to-end data science projects, develop custom Python and SQL solutions, improve machine learning models, and optimise classification and clustering performance while addressing data bias. Responsibilities include data transformation, quality assurance, insight generation, dashboard creation, client presentations, and contributing to the continuous improvement of analytics products and delivery processes.I am looking for high level candidates with a Master's or PhD in a quantitative discipline and 3+ years' experience in data science, analytics or consulting. Strong Python, SQL, statistical modelling and machine learning expertise are essential, alongside experience with pandas, NumPy, scikit-learn, NLP frameworks, transformers/LLMs, APIs and modern software engineering practices. Exposure to Azure DevOps, MLOps, Docker, Kubernetes or cloud AI platforms would be advantageous. Excellent communication skills, commercial awareness and the ability to simplify complex technical concepts for clients are key.This is an exceptional mandate - please let me know if interested. YOU MUST come from a Management Consultancy Background.

AI Engineer | GenAI & Agentic AIWe are looking for a highly skilled, hands-on AI Engineer to design and deliver enterprise-grade GenAI, Conversational AI, and Agentic AI solutions.This is primarily an Individual Contributor role (hands-on development / offshore team coordination), requiring strong expertise across GenAI, AI/ML, backend engineering, data validation, and React development.Key ResponsibilitiesDesign and deploy production-ready GenAI, RAG, and Agentic AI solutions.Build multi-agent workflows using LangChain, LangGraph, Haystack, or similar frameworks.Implement tool calling, contextual retrieval, memory management, and AI workflow automation.Develop RAG and hybrid search solutions using vector/graph databases.Perform data-quality validation, KPI/business-rule validation, reconciliation, and anomaly detection.Develop scalable Python APIs/backend services and React-based AI applications.Integrate AI solutions with enterprise systems and the Microsoft Azure ecosystem.Implement MLOps/LLMOps, CI/CD, monitoring, observability, guardrails, and Responsible AI practices.Review and coordinate technical deliverables from offshore development teams.Required SkillsStrong hands-on experience with GenAI, LLMs, Agentic AI, RAG, embeddings & prompt engineeringLangChain / LangGraph / HaystackPython, SQL, SparkReact.js, JavaScript / TypeScriptFastAPI / Flask / REST APIsVector & Graph DBs – Azure AI Search, Databricks Vector Search, Neo4jAzure OpenAI, Azure Databricks, ADFPyTorch / TensorFlowData validation & data-quality frameworksMLOps / LLMOps & production AI deploymentExperience building large-scale enterprise AI/ML solutionsGood to have: n8n, Microsoft Copilot ecosystem, Databricks Genie, Azure Functions, AKS, Redis, Bot Framework, API Management & Entra ID.

Required Technical SkillsStrong experience in Python and software development.Hands-on experience with LiteLLM, including:LiteLLM Proxy / GatewayMulti-model integrationModel routing and fallbacksLoad balancingAuthentication and access controlRate limiting and usage monitoringStrong understanding of LLM APIs and Generative AI concepts.Experience with one or more LLM providers:OpenAI / Azure OpenAIAnthropicGoogle GeminiAWS BedrockOpen-source LLMs such as Llama, Mistral, etc.Experience with RAG architecture and vector databases such as:PineconeWeaviateMilvusChromaFAISSElasticsearch / OpenSearchExperience with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar.Experience developing REST APIs using FastAPI, Flask, or similar frameworks.Good understanding of Docker and containerized deployments.Experience with cloud platforms such as Azure, AWS, or GCP.Familiarity with CI/CD, Git, Kubernetes, and production deployment practices.

SENIOR AI / MACHINE LEARNING OPPORTUNITY | DUBAI, UAEConjugate QADDS (Quantum | AI | Deep Tech | Data Centres | Space) is hiring as a specialist international talent network for the rapidly expanding Data Centre & AI industry.We are hiring professionals for opportunities across:USA | Australia | Japan | GCC | India | Southeast AsiaA leading AI company is expanding its senior leadership team and is looking for an accomplished AI / MACHINE LEARNING - Engineering leader to play a key role in shaping the next phase of growth.This is a senior engineering opportunity for a engineering leader who can combine deep technology understanding with strategic thinking, execution, innovation, and team leadership.Location: DUBAI, UAELevel: Senior Engineering RoleIndustry: Artificial Intelligence | Machine Learning | Deep TechWHAT YOU'LL WORK ONDepending on your expertise, opportunities may span:• Artificial Intelligence & Machine Learning• Generative AI & LLMs• Deep Learning• NLP / Computer Vision / Multimodal AI• Model Training & Evaluation• Inference & Optimization• AI/ML Infrastructure• MLOps & Production ML• Recommendation & Ranking Systems• AI Agents & Autonomous Systems• Data & ML PlatformsWHAT WE'RE LOOKING FORWe're interested in professionals with experience in one or more of the following:Python | C++ | PyTorch | TensorFlow | LLMs | Generative AI | Deep Learning | NLP | Computer Vision | Reinforcement Learning | MLOps | ML Infrastructure | Distributed Systems | AI PlatformsStrong software engineering fundamentals and experience taking AI/ML systems from research or prototype into production are highly valued.WHO SHOULD APPLY?We welcome applications from:AI EngineersMachine Learning EngineersML Software EngineersDeep Learning EngineersAI/ML EngineersApplied AI EngineersMLOps / ML Infrastructure EngineersResearch Engineers with strong engineering experienceBoth experienced and highly accomplished mid-career professionals are encouraged to apply.WHY THIS OPPORTUNITY?You'll have the opportunity to work within a high-calibre AI environment where engineering, research and product development intersect.If you're passionate about building AI systems that move beyond experimentation and into real-world scale, we'd like to hear from you.🌐 JOIN THE QADDS AI TALENT NETWORKEven if your background doesn't match this specific opportunity exactly, we would still like to connect with exceptional AI professionals.CONNECT WITH QADDSFollow the Conjugate QADDS LinkedIn Page:https://www.linkedin.com/showcase/qadds🔹 Join the QADDS Talent & Jobs Group:https://www.linkedin.com/groups/39735011/QADDS Talent & Jobs – LinkedIn GroupJoin the community to receive Data Centre, AI, Quantum, Deep Tech and Space technology career opportunities and industry updates.Quantum | AI | Deep Tech | Data Centres | Spacefor jobs acrossUSA | GCC | India | Japan | Australia | Southeast Asia

Job Purpose:Focuses on creating advanced machine learning models and AI-driven applications to solve complex business challenges. Thisposition ensures the development of robust, scalable, and efficient systems for real-world deployment. The engineer will collaborateacross teams to integrate AI solutions into production environments seamlessly.Key responsibilities1) Model & Solution EngineeringTranslate business problems into ML formulations; select suitable architectures (e.g., gradient boosting, transformers) with clear success metrics.Build end-to-end pipelines: feature extraction, training, hyperparameter tuning, and packaging models as reproducible artifacts.Optimize inference (quantization, distillation, mixed precision) for latency and throughput on CPU/GPU. Conduct evaluation beyond accuracy (calibration, fairness, cost-sensitive metrics, PR/ROC under imbalance).2) MLOps, Deployment & ObservabilityImplement model versioning, lineage, and experiment tracking; manage rollbacks and canary releases.Build real-time and batch inference services; integrate with message buses and vector databases.Monitor for schema checks, data drift, performance regression, and cost observability.Create alerting and autoscaling policies tied to SLAs, maintain incident runbooks for model services3) Data Engineering, Quality & GovernanceDesign data contracts; implement ETL/ELT pipelines (e.g., Spark/Databricks) with testing and backfills.Enforce data quality gates and schema evolution strategies to prevent mismatches.Apply privacy-by-design: PII handling, tokenization, and secure secrets management. Collaborate on cost-efficient data architectures (tiering, caching, Parquet/Delta formats)4) Experimentation, Product Integration & Stakeholder EnablementDesign experiments (A/B, counterfactual evaluation); define guardrails and success criteria with product teams.Integrate models via APIs/SDKs with business rules and fallbacks for graceful degradation. Produce clear documentation (model cards, decision logs) and present trade-offs to stakeholders.Qualifications & SkillsBachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.Proven experience in designing, training, and deploying machine learning models and AI solutions.Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).Hands-on experience with MLOps tools and practices (Docker, Kubernetes, MLflow, CI/CD pipelines).Proficiency in data processing and ETL tools (Spark, Databricks) and working with large datasets.Knowledge of model optimization techniques (quantization, distillation) and performance tuning for production environments.Familiarity with cloud platforms (Azure, AWS, or GCP) and scalable architecture design.Understanding of data governance, privacy standards, and compliance requirements.Strong analytical and problem-solving skills with attention to detail.Excellent communication skills to collaborate with cross-functional teams and present technical concepts clearly.

Position Title: Artificial Intelligence EngineerLocation : Dubai, UAEJob Description:We are looking for an experienced AI Engineer to build and deploy production-ready AI systems, intelligent agents, and scalable backend services.Key ResponsibilitiesDevelop production-grade Python/FastAPI services for AI applications.Build agentic workflows for chat, search, and RAG use cases.Work with LangChain, LangGraph, and LangSmith for agent development, tracing, and evaluation.Develop and optimize RAG pipelines, embeddings, and vector databases such as Qdrant and Milvus.Apply prompt engineering and agent testing methodologies.Monitor and optimize AI systems for accuracy, latency, cost, and scalability.Deploy AI services using Docker and cloud platforms.Required Qualifications3+ years of software engineering experience with strong Python/backend skills.1–2+ years of hands-on AI/ML production experience.Demonstrated proficiency in Python and software engineering best practices, with a focus on clean, maintainable, and production-quality code.Solid experience with NLP, Retrieval Augmented Generation (RAG), embeddings,deepshikha@hirerightt.com

We help the world run betterAt SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.What You'll BuildIn this role, you contribute to the design, development, and operation of AI-native enterprise applications within fast-moving, customer-embedded delivery teams. You bring solid engineering fundamentals and a growing command of AI and machine learning techniques, applying them to solve real-world business problems under the guidance of senior engineers and technical leads. This is a role for someone early in their AI engineering career who is hungry to learn, eager to contribute, and excited by the challenge of building production-grade solutions that make a tangible difference for enterprise customers.In This Role, You WillContribute to the development of production-grade, cloud-native applications integrating AI capabilities such as large language models, RAG pipelines, and agent-based components. Work within customer projects and cross-functional delivery teams, learning to understand business processes, technical landscapes, and customer needs. Implement features, components, and integrations under the guidance of senior engineers, maintaining code quality and adherence to engineering standards. Support prototyping, testing, and iteration of AI solutions in customer environments, adapting to feedback and evolving requirements. Participate in code reviews, technical discussions, and design sessions, actively developing your engineering skills and knowledge. Assist with monitoring, troubleshooting, and improving deployed solutions to ensure reliability and operational stability. Contribute to documentation, reusable components, and engineering best practices to support team productivity and knowledge sharing. Demonstrate a proactive learning mindset — staying current with AI/ML developments and applying new techniques and tools to improve solution quality. What You BringSolid foundational skills in software engineering, with proficiency in Python and hands-on experience in at least one cloud-native development environment. Growing understanding of AI and ML concepts, including familiarity with large language models, machine learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn), and API-based AI services. Exposure to data pipelines, MLOps concepts, or AI/ML model integration in application contexts. Ability to work collaboratively within a team, follow engineering standards, and take ownership of assigned tasks with a strong sense of accountability. Curiosity, adaptability, and a growth mindset — you actively seek feedback, learn from experience, and are motivated to grow quickly in a high-pace environment. Basic understanding of cloud platforms (e.g. AWS, Azure, GCP) and familiarity with tools such as Git, Docker, and CI/CD pipelines. Strong communication skills and the ability to work effectively within cross-functional teams and customer-facing settings. An interest in or early exposure to SAP AI technologies such as SAP AI Core or SAP Business Technology Platform (BTP) is a plus. Where You BelongYou will be part of a growing AI and industry expert team serving customers across the Americas, Europe, and Asia. We invest in the growth of our people at every level — and this role is built for someone who wants to accelerate fast. You will be surrounded by experienced engineers and AI practitioners who are committed to helping you develop. You will thrive here if you are curious, hardworking, and motivated by the opportunity to build real AI solutions for real enterprise customers — from day one.#SAPIndustryAICareersBring out your bestSAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.We win with inclusionSAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.Successful candidates might be required to undergo a background verification with an external vendor.AI Usage in the Recruitment ProcessFor information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.Please note that any violation of these guidelines may result in disqualification from the hiring process.Requisition ID: 457240 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations:

Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.Role OverviewWe are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle — from model design through deployment, optimization, and ongoing performance in production — and contributes to the technical direction of the AI platform.Key ResponsibilitiesArchitect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day oneBuild and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scaleOwn technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainabilityDesign and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applicationsImplement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelinesContinuously optimize model performance, inference latency, cost efficiency, and reliability across live systemsCollaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutionsMentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the teamContribute to strategic decisions around data architecture, AI infrastructure, and cloud platform directionWork with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimizationRequirements7 to 15 or more years of experience in software engineering, data science, or ML engineeringStrong background in product companies, scale-ups, or enterprise AI platformsProven track record of building production-grade AI systems, not solely notebooks or proof-of-concept workComfortable owning systems end-to-end from data through model through deployment through monitoringProduct-first engineering approach, not research-only profilesAdvanced Python engineering skills with strong systems thinking and a focus on production qualityComfortable with fast iteration cycles and deploying models into live environmentsAbility to work directly and confidently with stakeholders and product ownersFintech or financial services experience is an advantageTechnical SkillsMachine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelinesMLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacksCloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCPData Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architecturesWhy Join Us?Work with one of the world’s leading financial derivatives institutions. Competitive salary plus performance-based incentives. Access to a dynamic, international, and fast-growing environment. Strong opportunities for career progression within a global financial group. Be part of a business committed to innovation, excellence, and long-term growth. Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.

#TMC Middle East is looking for an Agentic AI Technical Consultant to join a leading company based in Jeddah, KSA.Role: Agentic AI Technical Consultant Location: Dubai, UAE Industry: Diversified group with operations across automotive, logistics, food/FMCG, hospitality, and healthcareAbout the Role Our client, a large diversified group investing in digital transformation across multiple business units, is seeking an Agentic AI Technical Consultant to design and deploy AI agent-based solutions that automate workflows and decision-making across the organization.Key ResponsibilitiesDesign, build, and deploy agentic AI workflows/solutions (multi-step, tool-using AI agents) for business process automationIntegrate AI agents with enterprise systems (SAP, analytics platforms, CRM, logistics/warehouse platforms)Work with LLM APIs/frameworks (e.g., LangChain, LangGraph, AutoGen, Semantic Kernel, or similar) to build production-grade agentsPartner with business stakeholders across verticals to identify automation opportunitiesBuild RAG pipelines, tool/function-calling integrations, and orchestration layersEnsure solutions meet security, governance, and data privacy standards for enterprise deploymentRequirements5+ years in AI/ML engineering, with hands-on experience in agentic AI/LLM application developmentStrong Python skills; experience with LLM orchestration frameworks and vector databasesExperience integrating AI solutions with enterprise systems (ERP/SAP experience a plus)Understanding of prompt engineering, RAG architectures, and agent evaluation/observabilityPrior consulting or cross-industry project experience preferredStrong communication skills to translate technical capability into business valuePlease apply ONLY if you are 100% comfortable with a strictly onsite arrangement — candidates not aligned on this will not be considered.Send your CV to abishake.kosman@tmc-employeneurs.com. Due to high application volumes, only shortlisted candidates will be contacted .

Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.Role OverviewWe are seeking an experienced AI Data Engineer to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.Key ResponsibilitiesCollaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV. Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation. Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences. Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks. Qualifications & RequirementsStrong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour. Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms. Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation. Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV. Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases. Previous exposure to ETL tools (e.g., dbt, AWS Glue) and cloud environments (preferably AWS, SageMaker). Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy. Why Join Us?Work with an industry-leading global financial institution. Competitive salary and comprehensive employee benefits. Opportunities for professional growth and career advancement. Collaborative, inclusive, and dynamic work environment. Commitment to innovation and professional excellence. Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.

Job DescriptionGenAI & Agentic AI Development :Design, develop, and deploy production-grade GenAI solutions using advanced LLMs such as OpenAI models.Implement Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured enterprise data.Design hybrid search architectures combining Vector DBs and Graph DBs such as Azure AI Search, Neo4j, and Databricks Vector Search.Develop reusable AI components and frameworks that can be leveraged across multiple enterprise AI use cases. Build Agentic AI workflows using frameworks such as LangChain, LangGraph, and Haystack, including:Multi-agent orchestration including planner, retriever, evaluator, and executor agents.Tool calling, function execution, and system-to-system automation.Short-term, long-term, and session-based memory management.Data Validation & QualityPerform end-to-end data validation before data is consumed by AI, ML, analytics, and decision-intelligence applications. Validate data completeness, accuracy, consistency, freshness, aggregations, calculations, and business-rule alignment across source systems and downstream applications.Work with business and data teams to validate KPIs, calculations, business rules, AI-generated insights, and recommendations before production release.Develop automated data-quality checks, validation frameworks, anomaly detection, and reconciliation processes.Identify data-quality issues and coordinate with Data Engineering and relevant teams for resolution.Ensure AI-generated insights and recommendations are based on validated and trusted enterprise data.Full-Stack AI & React Application DevelopmentTake hands-on ownership of end-to-end AI application development, from AI/ML services and APIs through user-facing applications. Design and develop modern, responsive react-based web applications for AI, analytics, and decision-intelligence use cases.Build interactive interfaces for AI insights, recommendations, conversational experiences, dashboards, visualizations, and actionable workflows.Integrate React applications with AI/ML services, enterprise APIs, data platforms, authentication services, and backend systems.Develop scalable backend services and APIs using Python and relevant API frameworks.Ensure frontend and backend applications meet enterprise requirements for performance, security, scalability, usability, and maintainability.Individual Contribution & Offshore Team CoordinationSpend approximately 90% of the role as a hands-on Individual Contributor, directly involved in architecture, coding, development, debugging, testing, optimization, deployment, and production support. Allocate approximately 10% of the role to coordinating and reviewing technical tasks delivered by the offshore team.Review offshore team deliverables to ensure alignment with requirements, solution design, coding standards, and expected quality.Perform code reviews, technical reviews, and functional validation of assigned offshore deliverables.Provide clarification on technical requirements and tasks where required to support offshore delivery.Track assigned technical tasks and highlight dependencies, quality issues, or delivery risks.Work collaboratively with offshore AI Engineers, Data Engineers, Data Scientists, and Frontend Developers on integrated solution delivery.Remain directly accountable for assigned hands-on development activities while supporting the quality and integration of offshore deliverables.Enterprise Integration & Cloud EngineeringDevelop and integrate AI-powered applications, chatbots, and agents within the Azure ecosystem. Integrate AI solutions with enterprise systems using APIs, event-driven architectures, and message brokers.Build secure and scalable services leveraging Azure App Services, Azure Functions, AKS, Azure Cache for Redis, and related services.Integrate applications with enterprise identity and access-management frameworks including authentication, authorization, RBAC, and data-level security.Work closely with Cloud, Digital, Data Engineering, Architecture, Security, and Business teams for end-to-end solution delivery.Production Readiness, MLOps & LLMOpsImplement guardrails for hallucination control, data privacy, security, responsible AI, and output validation. Ensure enterprise-grade governance including access control, auditability, monitoring, and compliance.Monitor production performance across availability, latency, accuracy, reliability, and scalability.Apply MLOps / LLMOps best practices across the lifecycle, including: Model and version management. Prompt versioning and rollback.CI/CD pipelines for AI applications.Automated prompt, retrieval, API, and regression testing.Monitoring, logging, tracing, and observability.Performance Optimization & Continuous ImprovementAnalyze AI application and agent performance using metrics such as accuracy, response quality, latency, adoption, and task completion. Optimize prompts, retrieval strategies, agent flows, APIs, database queries, and application performance based on actual usage.Identify and resolve performance bottlenecks across data, AI, backend, database, and frontend layers.Drive continuous improvement through experimentation, evaluation, monitoring, and user feedback.RequirementsStrong hands-on understanding of LLMs, transformers, embedding, prompt engineering, context engineering, RAG, and evaluation techniques. Experience building end-to-end GenAI and Agentic AI products from development through production deployment.Hands-on experience with LangChain, LangGraph, Haystack, n8n, and Microsoft Copilot ecosystem or similar frameworks.Practical experience designing multi-agent architectures and orchestrating reasoning, retrieval, tools, and actions.Strong experience with Vector and Graph Databases, including Azure AI Search, Neo4j, and Databricks Vector Search.Proven experience implementing RAG pipelines using structured and unstructured enterprise data.Strong experience with data validation, data-quality checks, reconciliation, KPI validation, and business-rule validation.Strong proficiency in Python, SQL, and Spark & Hands-on experience developing React / JavaScript / TypeScript applications.Experience developing APIs and backend services using FastAPI, Flask, or equivalent frameworksHands-on experience with PyTorch and/or TensorFlow.Experience working with large-scale AI/ML systems in production environments.Experience reviewing code and technical deliverables from distributed/offshore development teams.Strong problem-solving skills across AI, data, backend, frontend, and enterprise system integration.Azure & Data Platform ExperienceHands-on experience with relevant Azure and enterprise data technologies, including:Azure OpenAIAzure Data Factory (ADF)Azure DatabricksAzure AI SearchDatabricks GenieAzure AI Document IntelligenceAzure App ServicesAzure FunctionsAzure Kubernetes Service (AKS)Azure Cache for RedisAzure Bot Service / Bot FrameworkAPI ManagementMicrosoft Entra ID / Azure ADCI/CD and DevOps toolingJob DetailsRole Level: Mid-Level Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: https://techcarrot.ae/ Job Function: Data Science & AI Company Industry/Sector: IT Services and IT ConsultingWhat 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.

Who We AreBoston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.We Are BCG XWe’re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world’s most complex problems. Leveraging BCG’s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions.What You'll DoOur BCG X teams own the full analytics value-chain end to end: framing new business challenges, designing innovative algorithms, implementing, and deploying scalable solutions, and enabling colleagues and clients to fully embrace AI. Our product offerings span from fully custom-builds to industry specific leading edge AI software solutions.Our AI Software Engineers and Senior AI Software Engineers are part of our rapidly growing engineering team and help to build the next generation of AI solutions. You’ll have the chance to partner with clients in a variety of BCG regions and industries, and on key topics like climate change, enabling them to design, build, and deploy new and innovative solutions. Additional responsibilities will include developing and delivering thought leadership in scientific communities and papers as well as leading conferences on behalf of BCG X.We Are Looking For Dedicated Individuals With a Passion For Software Development, Large-scale Data Analytics And Redefining Organizations Into AI Led Innovative Companies. Successful Candidates Possess The Following Apply software development practices and standards to develop robust and maintainable software Actively involved in every part of the software development process Experienced at guiding non-technical teams and consultants in and best practices for robust software development Optimize and enhance computational efficiency of algorithms and software design Motivated by a fast-paced, service-oriented environment and interacting directly with clients on new features for future product releases Enjoy collaborating in teams to share software design and solution ideas A natural problem-solver and intellectually curious across a breadth of industries and topicsWhat You'll BringTechnologiesProgramming Languages: Python#BCGXjobBoston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.BCG is an E - Verify Employer. Click here for more information on E-Verify.

Please direct all resume submissions to QuantTalentASIA@mlp.com and reference REQ-30162 as the subject.Job Specification: Quant Research EngineerPreferred Candidate Profile Top-tier academic background from a globally top-20 university (e.g., MIT, Harvard, Princeton, Stanford, Caltech) PhD-level training in Computer Science, Engineering, Physics, Mathematics, or Statistics preferred Gold medal in a national or international olympiad (IMO, CMO, IOI, NOI, IPhO, CPhO) strongly preferred Prior experience at a top-tier quantitative trading firm or a leading AI/technology company preferred Demonstrated passion for applying AI — candidates who have built LLM-powered tools into their own research or engineering workflow stand outKey ResponsibilitiesCore Infrastructure Ownership Design, build, and maintain the firm’s core quant pipelines, data infrastructure, and research and production compute environments. Ensure the reliability, scalability, and performance of critical systems central to our research and trading activities. Drive the architectural vision for our next-generation data and compute platform — including how AI-native capabilities (LLM services, agentic workflows, retrieval infrastructure) are embedded into the research stack.Collaboration & Integration Partner directly with Quantitative Researchers and other development teams to understand their requirements and integrate new components into the core infrastructure. Act as a central point of expertise, facilitating the seamless flow of data and computation across teams and systems. Identify where AI can accelerate the research process — from literature ingestion and data exploration to signal prototyping — and build the tooling that makes it routine. Establish and enforce rigorous standards for system design, code quality, testing, and deployment.DevOps & AI-Augmented Operations Own the deployment, monitoring, and operational health of production and research systems. Implement robust observability, logging, and alerting frameworks; apply AI-assisted techniques (automated log analysis, anomaly detection, intelligent incident triage) to raise the bar on reliability. Drive infrastructure-as-code practices and automate operational workflows, leveraging AI coding agents and LLM tooling where they demonstrably improve velocity and quality.Qualifications & Experience 3–5 years of professional experience in a quantitative development role, focused on building and maintaining quantitative research and production pipelines. Alternatively, significant engineering experience in a fast-paced startup — or strong hands-on AI/LLM engineering experience (building production LLM applications, agentic systems, or AI-powered developertooling) — with demonstrated ownership of complex infrastructure will be considered in lieu of direct quant experience. Proven, end-to-end ownership of a significant piece of trading, research, high-performance, or AI infrastructure. Deep expertise in modern C++ and Python in a high-performance computing context. Demonstrable experience with large-scale data infrastructure (e.g., real-time/streaming and historical tick data). Strong background in cloud computing (AWS, GCP, or Azure) and parallel computing paradigms.Hard Skills & Technical Knowledge Broad knowledge of the technology landscape and the judgment to select the right tool for the problem (e.g., KDB+, Apache Spark, Dask, Redis). Practical experience applying LLMs and agentic workflows to real engineering or research problems — LLM APIs, agent frameworks, retrieval-augmented generation, and structured output pipelines — with sound judgment about where AI adds value and where determinism must be preserved. Proficiency with different database designs — SQL, NoSQL, and distributed file systems. Experience with containerization and orchestration technologies (Docker, Kubernetes). Strong experience with DevOps practices: infrastructure-as-code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, GitLab CI), and system observability — including familiarity with AI-assisted operations tooling.Soft Skills Exceptional Logical & Reflective Thinking: Ability to deconstruct complex problems and design elegant, effective solutions. Proactive Collaboration: A team player who thrives in a collaborative environment and builds strong partnerships. High Integrity: Takes initiative and ownership of projects, upholding rigorous ethical standards in handling sensitive data and models. Growth Mindset: Innate curiosity and commitment to continuous improvement — including genuine enthusiasm for the rapidly evolving AI landscape and a track record of adopting new tools ahead of the curve. Superb Communication: Can articulate complex technical concepts to both technical and non-technical stakeholders.

Role SummarySLICIT is on the forefront of integrating Web 3.0 technologies into the asset management and fintech sectors.We are seeking a Data Scientist with a pioneering spirit to harness vast datasets and apply analytical rigor in the realms of blockchain, tokenization, NFTs, and other Web 3.0 concepts.Your role will be instrumental in driving innovation through data-driven insights, particularly in optimizing asset management strategies, exploring fintech opportunities, and leveraging real-world assets through digital transformation.This position is tailor-made for someone who not only excels in technical and analytical capacities but also brings a wealth of business experience and industry knowledge in asset management, fintech, and the burgeoning field of digital assets.Reporting ToChief Technology OfficerEmployment TypeFull-TimeEssential Qualifications And SkillsMachine Learning and AI Expertise: The ideal candidate will possess a robust foundation in both theoretical and practical aspects of machine learning (ML) and artificial intelligence (AI), with a particular emphasis on applications within the financial sector. You should have hands-on experience designing, implementing, and validating a wide range of ML models, from traditional algorithms like Linear Regression, Decision Trees, and Clustering, to more advanced techniques including Neural Networks, Natural Language Processing (NLP), and Reinforcement Learning. Knowledge of Tools and Frameworks: Proficiency in using Python libraries such as Scikit-learn for machine learning model development and TensorFlow or PyTorch for deep learning applications. Experience with NLP tools like NLTK or spaCy to derive insights from textual data, which is particularly relevant in analyzing market sentiment or financial news. Familiarity with reinforcement learning frameworks such as OpenAI Gym, which can be applied to develop sophisticated trading algorithms that adapt and learn from the market’s dynamics. A track record of employing AI-driven analytics to forecast market trends, optimize investment portfolios, or enhance customer personalization and engagement in fintech solutions. Demonstrated Impact: Evidence of past projects where your ML and AI expertise directly contributed to significant business outcomes, such as improved investment returns, risk reduction, operational efficiencies, or customer satisfaction enhancements. The ability to quantify the impact of your work (e.g., percentage increase in investment performance, reduction in risk exposure) will be highly valued. Programming and Data Manipulation Proficiency: Adeptness in programming and data manipulation, critical for analysing complex datasets and developing scalable solutions. Core Programming Languages: Proficiency in Python is essential, given its widespread use in data science for everything from data manipulation with Pandas to complex machine learning with libraries like TensorFlow and scikit-learn. Expertise in R is also valuable, particularly for statistical analysis and visualization. Knowledge of SQL is crucial for querying databases and manipulating data stored in SQL databases. Data Manipulation Tools and Techniques: Candidates should demonstrate expertise in handling large datasets, employing techniques and tools for data cleaning, transformation, and aggregation. Experience with Python libraries such as NumPy and Pandas, or R packages like dplyr and tidyr, is expected. Version Control and Collaboration: Familiarity with version control systems, notably Git, is necessary for efficient collaboration within a team. This includes managing code repositories, branching, merging, and handling pull requests in platforms like GitHub or GitLab. Advanced Analytical and Statistical Skills: Expertise in statistical analysis, predictive modeling, and data mining, with a proven track record of leveraging these skills to drive business decisions. Education: A Master’s or PhD in Data Science, Computer Science, Mathematics, Statistics, or related field, with ideally coursework or projects focused on finance, blockchain, or digital assets. Nice-to-Have SkillsProgramming and Data Manipulation Proficiency in Scala or Java would be a plus, tailored towards data science applications in finance and asset management. Big Data Technologies: Familiarity with big data frameworks and cloud computing environments, enhancing data processing and analysis capabilities. Deep Learning Proficiency: Knowledge of deep learning applications in finance, such as predictive analytics for market trends or customer behaviour analysis. Data Visualisation Skills: Competence in using tools like Tableau or Power BI for creating intuitive data visualisations that convey complex information to stakeholders. Business Experience and Industry Knowledge: Some experience in asset management, fintech, or related sectors, with a keen understanding of market dynamics, regulatory environments, and the potential of digital transformation through Web 3.0 technologies. Blockchain and Web 3.0 Technologies: Deep understanding of blockchain fundamentals, smart contracts, tokenization of assets, NFTs, and their implications for asset management and fintech is a big advantage. Experience with platforms such as Ethereum, Hedera Hashgraph, and Polygon. In particular: Fundamental Blockchain Concepts: Candidates should have a solid grasp of key blockchain principles, including decentralized ledgers, consensus mechanisms, smart contracts, and cryptographic protocols. This knowledge is vital for analysing blockchain data and understanding the underlying technology of digital assets and transactions. Blockchain Platforms and Tools: Experience with major blockchain platforms such as Ethereum, for smart contract development, and ideally familiarity with newer platforms like Hedera Hashgraph, Polygon or Polymesh. Smart Contracts and DApps Development: While primarily a data-focused role, understanding the development and deployment of smart contracts and decentralized applications (DApps) can provide valuable insights into data sources and potential applications of blockchain in asset management and fintech. Knowledge of Solidity (for Ethereum) or other smart contract languages is a plus. Blockchain in Finance: Specific experience in applying blockchain technology to solve problems in finance, such as through tokenization of assets, implementation of NFTs for unique asset representation, or enhancing the security and efficiency of transactions. Industry Certifications: Certifications related to blockchain technology, data science, or finance, showcasing a commitment to ongoing professional development. Remuneration BenefitsCompetitive Salary: Reflective of the expertise and strategic importance you bring to the team. Comprehensive Benefits Package: Premium health insurance, retirement planning options, and generous vacation policies. Professional Development: Commitment to your growth through conferences, workshops, and certifications in emerging technologies and financial analysis. Innovative Work Culture: Be part of a dynamic team pushing the boundaries of technology in asset management and fintech. How To ApplyAre you excited by the challenge of transforming the asset management and fintech landscapes through Web 3.0 technologies? If you have a solid foundation in data science, your next career milestone awaits with us.Interested candidates should submit their resume, a comprehensive cover letter detailing your relevant experience, along with any notable projects, , and why you’re a fit for SLICIT, to careers@slicit.com with the subject line “Data Scientist Application”.Apply Now

Who We AreBoston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.We Are BCG XWe’re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world’s most complex problems. Leveraging BCG’s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions.What You'll DoOur BCG X teams own the full analytics value-chain end to end: framing new business challenges, designing innovative algorithms, implementing, and deploying scalable solutions, and enabling colleagues and clients to fully embrace AI. Our product offerings span from fully custom-builds to industry specific leading edge AI software solutions.As a Data Scientist and Senior Data Scientist, you'll be part of our rapidly growing team. You'll have the chance to apply data science methods and analytics to real-world business situations across a variety of industries to drive significant business impact. You'll have the chance to partner with clients in a variety of BCG regions and industries, and on key topics like climate change, enabling them to design, build, and deploy new and innovative solutions.Additional responsibilities will include developing and delivering thought leadership in scientific communities and papers as well as leading conferences on behalf of BCG X. Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.We Are Looking For Talented Individuals With a Passion For Data Science, Statistics, Operations Research And Transforming Organizations Into AI Led Innovative Companies. Successful Candidates Possess The FollowingComfortable in a client-facing role with the ambition to lead teams Likes to distill complex results or processes into simple, clear visualizations Explain sophisticated data science concepts in an understandable manner Love building things and are comfortable working with modern development tools and writing code collaboratively (bonus points if you have a software development or DevOps experience) Significant experience applying advanced analytics to a variety of business situations and a proven ability to synthesize complex data Deep understanding of modern machine learning techniques and their mathematical underpinnings, and can translate this into business implications for our clients Have strong project management skills What You'll BringTechnologiesProgramming Languages: Python#BCGXjobBoston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.BCG is an E - Verify Employer. Click here for more information on E-Verify.

Job Description: AI Software EngineerJob Location: UAERole SummaryThe AI Software Engineer will design, develop, and implement AI-enabled solutions that support data management, governance, and automation initiatives across enterprise workstreams. This role is responsible for building scalable AI applications and services that deliver metadata enrichment, data profiling, anomaly detection, duplicate detection, rule recommendations, remediation support, and intelligent automation within an approved sovereign AI environment.The ideal candidate combines strong software engineering practices with expertise in AI/ML, Generative AI, and data engineering to deliver production-grade AI solutions.Key ResponsibilitiesAI Solution DevelopmentDesign, develop, test, and deploy AI-powered applications and microservicesBuild scalable AI and machine learning solutions to automate business and data management processesDevelop reusable AI frameworks, APIs, and services for enterprise-wide adoptionOptimize AI models and applications for performance, reliability, and scalabilityMetadata Enrichment & Data IntelligenceDevelop AI-driven metadata enrichment capabilities to improve data discoverability and governanceBuild intelligent data profiling solutions to identify patterns, quality issues, and data relationshipsImplement automated classification and tagging mechanisms for enterprise datasetsAnomaly & Duplicate DetectionDesign and implement machine learning models for anomaly detection and data quality monitoringDevelop duplicate detection and entity-matching algorithms to improve data consistencyContinuously evaluate and enhance model accuracy and effectivenessAI-Assisted Rule Recommendation & RemediationBuild AI capabilities that suggest and optimize data quality rulesImplement recommendation engines that assist users in resolving data issuesDevelop intelligent remediation workflows and automated corrective actionsGenerative AI & AutomationDevelop LLM-powered solutions and AI agents to streamline business processesImplement prompt engineering, retrieval-augmented generation (RAG), and AI workflow orchestrationIntegrate Generative AI services into enterprise applications and platformsSovereign AI & ComplianceEnsure AI solutions operate within approved sovereign AI and security environmentsFollow responsible AI, privacy, governance, and compliance standardsImplement security controls, monitoring, and auditability for AI applicationsCollaboration & DeliveryWork closely with solution architects, data engineers, product owners, and business stakeholdersTranslate business requirements into technical AI solutionsParticipate in code reviews, testing, deployment, and production support activitiesMaintain technical documentation and promote engineering best practicesRequired QualificationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related field5+ years of software engineering experience with at least 2+ years developing AI/ML solutionsExperience delivering enterprise-scale AI applications in production environmentsStrong understanding of software development lifecycle (SDLC), CI/CD, and DevOps practicesTechnical SkillsProgramming & EngineeringPython (mandatory)Java, C#, or Node.jsREST APIs and Microservices ArchitectureGit, DevOps, CI/CD PipelinesAI & Machine LearningScikit-learn, TensorFlow, PyTorchMachine Learning Model Development and DeploymentAnomaly Detection and Pattern RecognitionNLP and Text AnalyticsGenerative AIAzure OpenAI Service / OpenAI APIsLarge Language Models (LLMs)Prompt EngineeringRetrieval-Augmented Generation (RAG)AI Agents and Workflow AutomationData TechnologiesSQL and NoSQL DatabasesData Profiling and Data Quality FrameworksData Governance and Metadata Management ToolsETL/ELT and Data Engineering ConceptsCloud & PlatformsMicrosoft Azure (Preferred)Azure AI FoundryAzure Machine LearningAzure DatabricksContainerization (Docker/Kubernetes)Preferred QualificationsExperience working in regulated, government, or sovereign cloud environmentsKnowledge of data governance, data quality, and master data managementMicrosoft Azure AI Engineer Associate (AI-102) or equivalent certificationExperience implementing Responsible AI and AI Governance frameworksKey CompetenciesStrong software engineering and system design skillsProblem-solving and analytical thinkingAbility to translate business needs into AI solutionsEffective stakeholder communicationInnovation mindset with focus on automation and continuous improvementStrong collaboration and teamwork skills

Job DescriptionWe are seeking experienced AI Engineers / Agentic AI Developers to design, develop, and deploy enterprise-grade AI solutions with a focus on Agentic AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The successful candidate will be responsible for building intelligent AI agents and workflows capable of reasoning, planning, task execution, and orchestration while ensuring all solutions are deployed in an on-premises environment using local AI models and tools.Key Responsibilities Gather, analyze, and translate business requirements into scalable AI and Agentic AI solutions. Design, develop, test, deploy, and maintain AI-powered applications and autonomous AI agents. Build Agentic AI workflows capable of reasoning, planning, task execution, and orchestration. Develop and integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures. Integrate AI solutions with enterprise applications, APIs, databases, cloud services, and on-premises systems. Optimize AI models, prompts, workflows, and application performance. Ensure AI solutions comply with enterprise security, governance, privacy, and Responsible AI standards. Prepare technical documentation, deployment guides, operational manuals, and knowledge transfer materials. Provide technical support, troubleshooting, performance tuning, and continuous improvements. Design and implement AI solutions using on-premises infrastructure, local models, and enterprise-approved AI tools. RequirementsBachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. 5+ years of software development experience, including 2+ years working with AI/Generative AI technologies. Strong experience with Python and AI application development. Hands-on experience with Large Language Models (LLMs) and prompt engineering. Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions. Experience building Agentic AI or multi-agent systems. Experience integrating AI applications with REST APIs, databases, and enterprise applications. Familiarity with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar. Experience working with vector databases such as Milvus, ChromaDB, FAISS, Pinecone, or equivalent. Knowledge of model deployment using Ollama, vLLM, Hugging Face Transformers, NVIDIA NIM, or similar on-premises inference platforms. Experience deploying and managing AI solutions in on-premises environments. Understanding of AI security, governance, privacy, and Responsible AI principles. Experience with Docker, Kubernetes, Git, and CI/CD pipelines is preferred. Strong analytical, problem-solving, communication, and documentation skills. Preferred Skills Experience with open-source LLMs such as Llama, Mistral, Qwen, Gemma, or DeepSeek. Experience with GPU infrastructure and AI model optimization. Knowledge of MLOps practices and AI monitoring. Experience integrating AI solutions with enterprise platforms such as SAP, ServiceNow, Microsoft 365, or other enterprise systems. Experience working in highly secure or regulated enterprise environments. This JD is aligned with your requirement that all AI use cases must run on-premises using local models and on-premises tools, making it suitable for enterprise or government projects.

Job PurposeJoin the Emirates Group Analytics Centre of Excellence (ACoE) and help shape the future of data science, artificial intelligence and advanced analytics across one of the world's leading aviation and travel organisations.As a Senior Data Scientist/ Senior AI Engineer, you will lead the design and delivery of innovative machine learning, optimisation and AI solutions for business that influence strategic decisions, improve operational performance and create exceptional customer experiences. You will work on complex challenges at scale while mentoring others and driving the adoption of AI and advanced analytics across the organisation.In This Role, You WillLead end-to-end AI initiatives from problem definition through to deployment and value realisation.Partner with business leaders to transform strategic challenges into scalable AI and analytics solutions.Design and implement advanced machine learning, optimisation and simulation models.Develop AI-powered capabilities leveraging GenAI, LLMs and Agentic AI technologies.Drive experimentation, model validation and performance measurement to ensure business impact and automate business decisions. Lead the development of reusable data science frameworks, libraries and production-ready solutions.Collaborate closely with engineering teams to operationalise machine learning and AI products.Mentor and coach junior data scientists while helping shape best practices across the wider analytics community.Champion innovation and identify emerging technologies that can create competitive advantage.QualificationTo be considered for this role, you must meet the below requirements:QualificationsMSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science or a related quantitative discipline.Experience4-7+ years of experience delivering advanced analytics, machine learning, optimisation or AI solutions in large, complex organisations.Knowledge & SkillsExpert knowledge of machine learning, statistical modelling and advanced analytics.Strong experience with GenAI, LLMs, Agentic AI and emerging AI technologies.Hands-on AI Engineering experience including model deployment, Agentic orchestration frameworks, evaluation frameworks, observability and monitoring, RAG architectures and scalable AI application development.Experience with optimisation frameworks such as Gurobi, FICO or CPLEX.Strong programming skills in Python and SQL.Experience with Git, Docker, CI/CD pipelines and MLOps practices.Proven experience deploying production-grade analytics and AI solutions.Strong stakeholder management and communication skills with the ability to influence senior leaders.Experience mentoring and developing technical talent.A commercial mindset focused on delivering measurable business value through AI and analytics. Preferred ExperienceExperience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.Experience evaluating, monitoring and governing production AI systems.Understanding of cloud-native AI platforms and modern AI engineering best practices.Salary & benefitsJoin us in Dubai and enjoy an attractive tax-free salary alongside exceptional travel, healthcare and lifestyle benefits. You'll work on some of the most exciting AI, data science and optimisation challenges in the industry while helping shape the future of analytics at global scale.

Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.We're building a cutting-edge AI team. As an Applied AI Engineer, this role suits someone with the technical depth of a backend engineer who is specifically interested in applied AI and how it can improve the energy experience for our customers and our internal operations. You'll work on consumer features such as the Energy Co-Pilot and speedy onboarding (using VLM and LLM tools) and build AI tools that make teams across Fuse more productive.ResponsibilitiesDesign, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)Build and optimise internal AI tools that make the whole company more productive, with a focus on automation and enhancing workflowsCollaborate with backend engineers and data scientists to integrate AI-driven features into our platformsCollaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricingImprove AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecastsStay up to date with the latest advancements in applied AI and machine learning and apply them to real-world problems in the energy spaceMonitor the performance of AI tools and models, ensuring they run efficiently and effectivelyRequirementsMinimum 3 years of engineering experienceProven experience as a backend engineer with a strong interest and practical experience in applied AI or machine learningStrong programming skills in Python (or similar) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into productionSolid understanding of cloud technologies, containerisation and building scalable AI applicationsAbility to integrate AI/ML models into real-world applications, focusing on usability and performanceStrong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environmentExperience working with large datasets, particularly in relation to demand and supply forecastingBonus: experience or strong interest in energy markets and trading strategies; understanding of weather forecasting, energy demand patterns and production modelling; exposure to NLP or related fieldsBenefitsCompetitive salary and eligibility for equityBiannual bonus schemeFully expensed tech to match your needsPrivate health insuranceBreakfast and dinner allowance for office-based employeesAs we hire globally, benefits may vary by location.

Hyderabad, India / Dubai, UAEFull-timeApply to JobAbout The RoleWe are looking for a highly motivated Machine Learning Engineer / Data Scientist to join our dynamic team. In this mid-level role, you will leverage your expertise in data science and machine learning to design, build, and deploy innovative models and solutions that address real-world challenges.You will collaborate with cross-functional teams, including data engineers, product managers, and software developers, to turn complex datasets into actionable insights and build machine learning solutions that drive business value. This is a fantastic opportunity to work on impactful projects, expand your skill set, and contribute to cutting-edge advancements in AI and data science.Key ResponsibilitiesModel Development: Design, train, and evaluate machine learning models to solve business problems such as classification, regression, clustering, and recommendation.Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering to optimize model performance.Model Deployment: Deploy machine learning models into production environments, ensuring scalability and robustness.Algorithm Selection: Research and implement state-of-the-art algorithms and methodologies to enhance model accuracy and efficiency.Collaboration: Collaborate with data engineering teams to build data pipelines and ensure efficient data flow for machine learning workflows.Visualization and Reporting: Create clear and actionable visualizations and reports to communicate findings and results to stakeholders.Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models as needed.Tool Development: Build tools and frameworks to enable rapid experimentation and iteration of machine learning models.Documentation: Maintain comprehensive documentation for models, experiments, and processes.QualificationsEducation:Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent experience).Technical SkillsStrong programming skills in Python, R, or similar languages.Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.Experience with big data technologies such as Spark, Hadoop, or similar.Knowledge of cloud platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).Familiarity with MLOps practices and tools for CI/CD in machine learning workflows.Understanding of data visualization tools like Matplotlib, Seaborn, or Tableau.Strong grasp of statistical methods, probability, and optimization techniques.Experience3–5 years of experience in machine learning, data science, or a related field.Proven experience building and deploying machine learning models in production.Experience with natural language processing (NLP), computer vision, or time-series analysis is a plus.Soft SkillsStrong problem-solving and analytical thinking abilities.Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.Ability to work independently and collaboratively within a team.Curiosity and eagerness to stay updated on the latest advancements in machine learning and AI.About The CompanyDatamaze is a dynamic company specializing in AI, Data, and Analytics consulting services. We are dedicated to transforming businesses by leveraging the power of data and artificial intelligence. With a team of industry experts in technology, business strategy, and data science, Datamaze offers a range of services including data strategy development, AI model creation, advanced analytics, and data visualization. Our approach is client-centric, focusing on creating customized solutions that address unique business challenges and objectives. The team, comprising data scientists, AI experts, strategists, and engineers, is committed to continuous learning and innovation.Datamaze positions itself as a trusted partner for businesses looking to navigate the complex data and AI landscape, aiming to optimize operations, inform decision-making, and maintain a competitive edge.Apply Now

Müller's Solutions is excited to announce an opening for a Google Cloud AI Specialist to drive our artificial intelligence initiatives leveraging Google Cloud Platform (GCP). In this role, you will be responsible for designing and implementing AI and machine learning solutions to help transform our data into actionable insights and enhance decision-making processes across the organization.Key Responsibilities:Develop and deploy machine learning models using GCP tools such as AI Platform, TensorFlow, and AutoMLCollaborate with cross-functional teams to identify business needs and translate them into AI and ML project requirementsConduct data analysis to prepare datasets for model training and evaluation while ensuring data quality and integrityImplement and optimize AI workflows that facilitate real-time data processing and inferenceStay updated on the latest advancements in AI and machine learning technologies to continuously improve our offeringsProvide technical guidance and support to teams on best practices for using Google Cloud AI servicesDocument AI project implementations, model performance evaluations, and ongoing maintenance proceduresContribute to developing educational materials and training sessions on AI capabilities for staff and stakeholdersMonitor and assess the performance of deployed AI models, making adjustments as necessary to ensure effectivenessRequirementsRequirements:Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field3+ years of experience in machine learning or AI solutions development, preferably using Google Cloud PlatformProficient in programming languages such as Python or R, with a strong understanding of machine learning libraries (e.g., TensorFlow, scikit-learn)Experience with cloud-based AI technologies, especially GCP services like Vision AI, Natural Language API, and AutoMLStrong knowledge of data preprocessing, feature engineering, and model evaluation techniquesAbility to work with large datasets, utilizing BigQuery or similar data processing toolsExcellent problem-solving skills and a strong analytical mindsetCapable of communicating complex technical concepts to diverse audiences effectivelyPreferred Qualifications:Google Cloud certifications (e.g., Google Cloud Professional Data Engineer or Google Cloud Professional Machine Learning Engineer) are a plusExperience with MLOps practices and tools for model deployment and managementFamiliarity with DevOps practices as they relate to AI and machine learningA background in statistics or applied mathematics is desirableBenefits1- Attractive Package.2- Family Benefits.3- Visa.4-Air Tickets.

Please submit resumes to QuantTalentEUR@mlp.com and reference REQ-30088.Preferred Candidate Profile Top-tier academic background from a globally top-20 university (e.g., MIT, Harvard, Princeton,Stanford, Caltech) PhD-level training in Computer Science, Engineering, Physics, Mathematics, or StatisticsPreferred Gold medal in a national or international olympiad (IMO, CMO, IOI, NOI, IPhO, CPhO)strongly preferred Practical, hands-on experience with large-scale, end-to-end deep learning at a top-tier quantitativeTrading Firm Or a Leading AI/technology Company PreferredKey Responsibilities Design and build the firm’s core deep learning pipelines for applied quantitative alpha research—from data preparation and distributed training through evaluation and production deployment. Drive a significant part of the research agenda using applied deep learning techniques, owning thefull empirical loop: problem formulation, model design, training, validation, and performanceattribution. Uphold rigorous research discipline in a low signal-to-noise domain — strict out-of-samplehygiene, leakage prevention, and honest benchmarking against simpler baselines. Act as the firm’s central point of deep learning expertise: advise on architecture selection andtraining diagnostics, review model designs, and set standards for how models are evaluatedand promoted. Facilitate the seamless flow of model fitting and model computation across teams and systemsthrough standardized training and inference interfaces and reusable components.Qualifications & Experience 3–5 years of professional experience applying deep learning to large-scale problems, ideally inquantitative finance. A strong PhD research record plus hands-on experience training largemodels at a leading AI/technology company will be considered in lieu of direct quant experience. Proven end-to-end ownership of the deep learning model lifecycle on at least one significantproduction system or published research line. Deep expertise in Python and a modern DL framework. Hands-on experience with large-scale model training: distributed/multi-GPU training,mixed precision, and throughput profiling and optimization. Strong foundations in statistics, optimization, and machine learning theory.Hard Skills & Technical Knowledge Command of modern deep learning architectures, and the judgment to know when a simplermodel should win. Practical technique for low signal-to-noise learning: regularization, ensembling, and validationprotocols that survive out-of-sample. Experience with large-scale datasets — efficient columnar formats, streaming data loaders,and point-in-time-correct dataset construction. Fluency with experiment-management tooling: experiment tracking, hyperparameter optimization,and reproducible research environments. Working knowledge of C++ or CUDA-level optimization a plus; familiarity with LLM toolingas a research accelerant a plus.Soft Skills Research Taste & Rigor: Designs clean experiments and kills ideas quickly when theevidence says so. Proactive Collaboration: Builds strong partnerships across research and engineering. High Integrity: Upholds rigorous ethical standards in handling sensitive data and models. Growth Mindset: Stays current with a fast-moving field and adopts what works. Superb Communication: Explains model behavior and uncertainty to technical and nontechnicalaudiences.

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 Lead 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 8+ 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.

Job PurposeJoin the Emirates Group Analytics Centre of Excellence (ACoE), where data, AI and innovation power decisions across one of the world's most recognised aviation and travel brands.As a Data Scientist/AI Engineer, you will solve complex business challenges using machine learning, advanced analytics, GenAI and Agentic AI. Working across commercial, operational and customer domains, you will transform vast amounts of data into actionable insights, intelligent products and measurable business outcomes.This is an opportunity to work on real-world, large-scale problems while helping shape the future of AI and data-driven decision making at Emirates Group.In This Role, You WillDevelop and deploy machine learning, Agentic AI and analytics solutions that drive measurable business impact.Analyse large structured, semi-structured and unstructured datasets to uncover insights and opportunities.Build predictive, prescriptive and optimisation models to solve business challenges across the Emirates Group.Partner with stakeholders to translate complex business questions into scalable data science solutions.Create visualisations, dashboards and analytical tools that support decision-making.Contribute to the development of reusable libraries, frameworks and production-ready data science assets.Apply experimentation techniques including A/B testing, segmentation and customer analytics.Collaborate with engineers, analysts and product teams in an agile delivery environment.Support the development and deployment of AI-powered products and intelligent automation capabilities.QualificationTo be considered for this role, you must meet the below requirements:QualificationsMSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science, Economics or a related quantitative discipline.Experience2-4+ years of experience delivering advanced analytics, machine learning or AI solutions in a commercial environment.Knowledge & SkillsStrong hands-on experience across the modern Data Science ecosystem.Experience developing and deploying Machine Learning, GenAI, LLM and Agentic AI solutions.Experience with AI Engineering practices including model deployment, monitoring, evaluation, prompt and context engineering and scalable AI application development.Proficiency in Python, SQL and modern analytical toolsets.Experience with Sparkor distributed data processing technologies.Experience with Git, Docker, CI/CD and MLOps workflows.Experience building reusable libraries, APIs or production-grade data science solutions.Strong problem-solving mindset with the ability to communicate technical concepts to non-technical audiences.Experience delivering solutions in complex, fast-paced environments. Preferred ExperienceExperience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.Experience evaluating, monitoring and governing production AI systems.Understanding of cloud-native AI platforms and modern AI engineering best practices.Salary & benefitsJoin us in Dubai and enjoy an attractive tax-free salary, industry-leading travel benefits, and access to one of the most exciting AI and data environments in the region. Alongside discounted flights and hotel stays worldwide, you'll have the opportunity to work on high-impact projects at global scale while advancing your career with Emirates Group.

We help the world run betterAt SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.What You’ll BuildIn this role, you'll lead the design and delivery of production-grade ML and generative AI systems that solve complex product and business problems at scale. You'll own architecture and implementation across data pipelines, feature stores, training workflows, model-serving infrastructure, online experimentation, and observability.You'll drive advanced use cases across deep learning, NLP, ranking, recommendation, forecasting, semantic retrieval, and LLM applications, including RAG, tool use, evaluation harnesses, and safety controls. Your work will directly shape performance, reliability, latency, and cost efficiency in live environments. You’ll guide technical direction on topics such as model selection, distributed training and inference, GPU utilization, model compression, prompt and retrieval optimization, drift detection, retraining strategy, and responsible AI controls. You’ll mentor other engineers and turn best practices into reusable patterns and platform capabilities.What You BringYou bring expert-level programming skills in Python, along with strong software engineering expertise in languages such as Java or Go, enabling you to build scalable, production-grade systems You have deep knowledge of machine learning, deep learning, and optimization techniques across structured data, NLP, search, ranking, and recommendation problems You have extensive experience designing and operating end-to-end ML systems, from data ingestion and experimentation to deployment, observability, and lifecycle management You bring strong hands-on experience with modern ML and LLM tooling (e.g., PyTorch, TensorFlow, scikit-learn), including fine-tuning, evaluation, orchestration, and model serving You have practical experience building generative AI applications using embeddings, vector databases, RAG pipelines, agent workflows, prompt engineering, and guardrails You bring deep expertise in MLOps and platform engineering, including model registries, feature stores, CI/CD, infrastructure as code, experiment tracking, and automated validation You have a strong architectural understanding of distributed systems, event-driven services, streaming data, and cloud-native ML platforms, with the ability to optimize for performance, scalability, reliability, and cost You define robust evaluation and governance strategies, including offline benchmarking, online experimentation, hallucination analysis, model risk assessment, and responsible AI practicesAbout YouYou bring 7-9+ years of experience in software engineering and machine learning, with a track record of leading and delivering complex, production-scale AI systemsYou combine strong product judgment with technical depth, translating ambiguous business problems into scalable, high-impact AI solutions You thrive in complex, fast-moving environments and bring clarity, ownership, and strategic thinking to drive long-term platform successWhere You BelongYou will be part of a growing team of AI and industry experts dedicated to serving customers across the Kingdom of Saudi Arabia / United Arab Emirates. We are building a collaborative, high‑impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets.This team thrives on working together to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real‑world impact matters. This is a place for people who enjoy building something new. You will thrive here if you are customer‑centric, motivated by meaningful outcomes, and comfortable navigating ambiguity in a fast‑evolving AI landscape.About The TeamWe are a team of engineers passionate about building valuable, scalable AI frameworks that drive real business impact. We thrive on solving challenging problems, innovating with cutting-edge technologies, and collaborating closely to deliver AI systems that are reliable, high-performing, and ready for production. Our team values ownership, technical excellence, and creating solutions that stand the test of scale and complexity.Bring out your bestSAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.We win with inclusionSAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.Successful candidates might be required to undergo a background verification with an external vendor.AI Usage in the Recruitment ProcessFor information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.Please note that any violation of these guidelines may result in disqualification from the hiring process.Requisition ID: 450236 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations:

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.

Role SummaryWe are looking for a skilled AI Engineer to design, build, and deploy intelligent solutions using Large Language Models (LLMs), Natural Language Processing (NLP), and Computer Vision (CV). This role involves developing practical AI applications such as conversational agents, document analysis systems, image processing tools, and automation solutions. The ideal candidate is hands-on, product-driven, and enthusiastic about leveraging AI to solve real-world business challenges at scale.Key ResponsibilitiesModel DevelopmentDesign, build, and optimize AI models across multiple domains, including:NLP (text understanding, chatbots, document processing)LLM-driven applications (RAG, agents)Computer Vision (object detection, OCR, video analytics)Fine-tune and customize pre-trained models for specific domain requirementsExplore and evaluate new architectures and techniques to enhance model performanceData ManagementGather, preprocess, and curate datasets for NLP and Computer Vision projectsApply data augmentation strategies for text and image dataMaintain high data quality and relevance to support effective model training and evaluationDeployment & IntegrationDeploy and integrate AI models into production environmentsMonitor model performance and implement continuous improvement strategiesOptimize deployment pipelines for efficiency and scalabilityMonitoring & OptimizationMonitor model performance and identify areas for improvementImplement monitoring and alerting systems to detect performance issuesOptimize model inference pipelines for latency and cost efficiencyCollaborationPartner with product, engineering, and business teams to deliver AI-powered solutionsContribute to system design and architectural decisionsPromote knowledge sharing and best practices within the teamContinuous InnovationKeep abreast of the latest developments in LLMs, NLP, and Computer VisionAssess, adopt, and integrate new tools, frameworks, and methodologies to drive innovationRequirementsBachelor's degree in Computer Science, AI, Machine Learning, or a related field, or equivalent practical experienceAt least 2 years of experience in AI/ML engineering, with a focus on NLP, LLMs, or Computer VisionProven hands-on experience designing, building, and deploying real-world AI systemsExperience with multimodal AI (text and image)Familiarity with vector databases such as FAISS, Milvus, or PineconeExperience with real-time inference systemsBasic understanding of Docker and KubernetesTechnical SkillsCore SkillsProficient in Python with experience in deep learning frameworks (PyTorch, TensorFlow)Strong understanding of machine learning, deep learning, neural networks, and model optimizationAI / LLM / NLPHands-on experience with LLMs (GPT, LLaMA, Mistral), prompt engineering, fine-tuning, and RAG pipelinesFamiliar with Hugging Face Transformers, LangChain, LlamaIndex; optional experience with spaCy/NLTKComputer VisionExperience with image processing, CV models, and libraries such as OpenCV and torchvisionFamiliar with object detection, classification, OCR, and segmentation tasksDeployment & MLOpsSkilled in model serving with FastAPI, NVIDIA Triton, or similar frameworksExperience with monitoring/observability tools (Grafana, Prometheus)Knowledge of deploying AI models on cloud platforms (AWS, GCP, Azure)What We OfferCompetitive Compensation: Enjoy a salary package tailored to your skills and experience, along with performance-based bonusesComprehensive Benefits: Visa processing and UAE mandated benefitsWork-Life Balance: Generous holidays and bonus policiesTop-Tier Equipment: Stay productive with the latest tools, including a MacBook and iPhoneCollaborative Culture: Immerse yourself in a dynamic, inclusive work environment that fosters growthEmployee Support: Bi-Annual travel/home visit reimbursements

Social Media Manager (AI Content) Own the social presence of an AI company that ships real products, not screenshots. Dubai, UAE (onsite/hybrid). Full-time. Direct employment. Visa sponsorship plus relocation support. About Valida Global LLC FZ: we build "HQ operating systems", the AI-powered operational and back-office layer companies plug into to run their business. Agents that handle real workflows, retrieval over messy internal data, and integrations that connect a client's tools into one system that actually takes action, not just chats. We build on Claude (Anthropic) and the Anthropic API, and we ship to real clients. We are based in Dubai's Meydan Free Zone, we employ our team directly, and we sponsor full UAE employment visas. What you will do: You will run our social channels end to end: LinkedIn, Instagram, TikTok, and X. That means building the content calendar, writing the hooks, cutting the short-form video, briefing design, publishing, and reporting on what actually moved. You will sit close to the product and the founders, turn what we are building into content people want to watch, and use AI tooling to produce at a volume a traditional team cannot match. You will also handle community: replies, DMs, and routing real inbound to the sales team. This is a builder role, not a scheduler role. If you want to post someone else's approved copy three times a week, this is not it. What you get: AED 6,000 to 9,000 per month depending on experience, full UAE employment visa, medical insurance, and relocation support. You will work daily with Claude and the Anthropic API on a product people are actually paying for, and there is room to grow into owning paid media and building out a team as we scale. How to apply: Hit Quick Apply, and include one post you would publish for Valida in your first week. Any format, any platform. We care more about that than your CV.

LLM Engineer (Junior) Start your AI career building Claude-powered operational systems that real companies run on — and grow fast. 📍 Dubai, UAE (onsite/hybrid) · Full-time · Direct employment · Visa sponsorship + relocation support About Valida Global LLC FZ Valida Global LLC FZ builds “HQ operating systems” — the AI-powered operational and back-office layer that companies plug into to run their business. Think agents that handle real workflows, retrieval over messy internal data, and integrations that connect a client’s tools into one system that actually takes action, not just chats. We build on Claude (Anthropic) and the Anthropic API, and we ship to real clients. We’re based in Dubai’s Meydan Free Zone, we employ our engineers directly, and we sponsor full UAE employment visas.