Machine Learning Jobs in Dubai

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.

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.

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.

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.

Job Requisition ID: 180608Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organization to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every dayUse Data Science to Predict, Improve, and Transform Healthcare OutcomesAl-Futtaim Health is seeking an experienced Healthcare Data Scientist – Machine Learning & Clinical Analytics to join our HealthHub Corporate Office in Dubai Festival City.This is a specialist data science role focused on predictive modelling, machine learning, clinical analytics, healthcare data integration, and AI-driven decision support across our growing healthcare network.Important: This is not a Data Analyst, BI Analyst, Reporting Analyst, Power BI Developer, or dashboard-only role.We are looking for a hands-on Data Scientist who has personally built, trained, tested, and evaluated predictive models using real healthcare datasets such as electronic health records, claims, pharmacy data, laboratory data, clinical activity data, or healthcare operational data.The purpose of this role is to move beyond reporting what has already happened and help HealthHub predict what may happen next, optimise patient pathways, improve clinical decision-making, and support better healthcare outcomes.About The RoleAs a Healthcare Data Scientist, you will design, develop, and evaluate machine learning models and advanced analytics solutions that support clinical, operational, financial, and strategic decision-making.You will work closely with clinical leadership, medical directors, operations teams, finance, IT, health informatics, and compliance stakeholders to transform complex healthcare data into predictive insights and practical healthcare solutions.The role requires a strong combination of healthcare domain knowledge, statistical modelling, machine learning, Python or R, advanced SQL, healthcare data standards, and responsible healthcare AI practices.Key ResponsibilitiesBuild, train, test, and evaluate predictive machine learning models for healthcare use cases.Develop models that support clinical risk prediction, patient outcomes, utilisation, readmission risk, claims analytics, revenue cycle optimisation, and care pathway improvement.Analyse and model healthcare datasets including EHR, clinical, claims, pharmacy, laboratory, patient activity, and healthcare operational data.Apply statistical and machine learning techniques such as logistic regression, survival analysis, classification, clustering, random forest, XGBoost, and other predictive modelling methods.Prepare analytical datasets using advanced SQL, including cohort building, joins, window functions, longitudinal patient data, feature engineering, and data quality checks.Work with healthcare data standards and coding systems such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, and FHIR.Support clinical decision support, predictive analytics, healthcare AI, and data governance initiatives.Collaborate with clinicians and operational stakeholders to translate data science outputs into practical healthcare workflows.Evaluate model performance using appropriate metrics such as AUC, precision, recall, F1 score, sensitivity, specificity, calibration, and explainability methods.Ensure healthcare data privacy, ethical AI use, and compliance with relevant healthcare data governance requirements.Essential RequirementsCurrently residing in the UAE.Bachelor’s Degree in Data Science, Computer Science, Statistics, Biostatistics, Biomedical Engineering, Health Informatics, or a related quantitative discipline.Minimum 2–5 Years’ Experience In Data Science.Minimum 2 years’ experience working with healthcare datasets, clinical analytics, health informatics, healthcare AI, health insurance data, or health-tech data.Proven hands-on experience building predictive models or machine learning solutions.Advanced Python or R experience for data science, machine learning, statistical modelling, feature engineering, and model evaluation.Advanced SQL experience for complex extraction, analytical dataset creation, cohort building, and healthcare data preparation.Experience working with healthcare datasets such as EHR, clinical, claims, pharmacy, laboratory, patient activity, or healthcare operational data.Understanding of healthcare coding or interoperability standards such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, or FHIR.Ability to communicate technical outputs clearly to clinical, operational, finance, and leadership stakeholders.Highly DesirableMaster’s Degree or PhD in Health Data Science, Biostatistics, Computational Biology, Data Science, or a related field.Experience with UAE healthcare data environments, DHA regulations, NABIDH, Malaffi, or healthcare data residency requirements.Experience working within a hospital, clinic network, healthcare group, health insurance provider, health-tech company, clinical analytics team, or health informatics environment.Experience with clinical decision support systems.Experience With SHAP, LIME, Or Other Model Explainability Methods.Experience with Power BI, Tableau, Plotly, or Dash to communicate data science outputs to leadership.Who This Role Is Not ForThis role is unlikely to be suitable if your experience is primarily focused on:Power BI dashboards only.KPI reporting only.Excel reporting.SQL extracts without modelling.Descriptive analytics only.Claims audit reporting only.General business intelligence without predictive modelling.Data analysis without machine learning or statistical model development.Candidates must be able to demonstrate hands-on experience building data science or machine learning models using healthcare datasets.Why Join Al-Futtaim Health?Work from HealthHub Corporate Office in Dubai Festival City.Opportunity to shape healthcare AI and predictive analytics across a growing healthcare network.Work with clinical, operational, finance, and leadership stakeholders.Exposure to healthcare datasets and real-world clinical decision-making.Opportunity to support patient outcomes, operational efficiency, and healthcare innovation.Competitive salary and benefits package.Career development within one of the UAE’s leading healthcare organisations.About Al-Futtaim HealthcareWe Hear Your Ambition.For over 90 years, the Al-Futtaim Group has been bringing the world’s leading brands of lifestyle watches, cars, home furnishings and fashion to the UAE. The Group has now introduced a whole new way of holistic healthcare through HealthHub Clinics by Al-Futtaim, its multi-speciality chain of more than 20 clinics in Dubai with over 25 specialties offering the right combination of advanced diagnostics, proven medical expertise and specialised services.What gives our clinics an edge is that as a part of the Al-Futtaim Group, you can expect world-class quality standards, with access to the best medical services and facilities within a healing environment. It’s a new way of healthcare that’s designed to meet a patient’s needs with a complete range of smart healthcare solutions. As testimony to this, only recently, we’ve earned a rare milestone of being the only primary healthcare network in the UAE to receive the Gold Seal by a reputed international body: Accreditation Canada.As trusted partners to health, we at HealthHub Clinics adopt evidence-based learning that enables us to listen to our patients more carefully. It helps us in treating the cause and not just the symptoms, while applying global best practices to ensure quality of care for every family member. Most of all, we adopt a patient-centric approach to healthcare that is reflected in the promise of our core belief: “We Hear You.”

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

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 DescriptionAl Ghurair Investment (AGI) is seeking an experienced and forward-thinking Senior Specialist – Artificial Intelligence (AI) to join our data and innovation team. The ideal candidate will have a strong background in applied AI and data science, with hands-on experience in developing, deploying, and optimizing Large Language Model (LLM)-based and Agentic AI solutions. This role is central to AGI’s AI transformation journey, enabling the design of intelligent systems, automation workflows, and generative AI capabilities that enhance decision-making and operational efficiency across the enterprise.ResponsibilitiesDesign and deliver end-to-end AI/ML solutions — from problem definition through production deployment — using LLMs, RAG, and agentic frameworks to solve business problems.Build and optimize AI pipelines for data ingestion, retrieval, and contextual reasoning at enterprise scale.Develop, fine-tune, and evaluate models for use cases like document intelligence, process automation, forecasting, churn prediction, and business reporting.Apply exploratory data analysis, statistical techniques, and ML methods (time-series, regression, tree-based models like XGBoost) to uncover insights and guide modelling decisions.Awareness of MLOps practices — model versioning, monitoring, drift detection, retraining, and CI/CD — to ensure scalable, reliable production deployments.Collaborate with data engineers, developers, platform teams, and business stakeholders to translate requirements into deployable solutions and drive measurable impact.Maintain AI architectures, workflows, and documentation while championing ethical, transparent, and fair AI aligned with governance standards.Continuously assess emerging AI trends and integrate best practices into the innovation roadmap.QualificationsEDUCATION & CERTIFICATIONS:Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.Professional certifications in AI/ML or cloud-based AI solutions preferred.Additional credentials in Generative AI, Machine Learning Operations (MLOps), or Responsible AI are a plus.Experience5–8 years of professional experience in Data Science, Machine Learning, or Applied AI roles.Proven expertise in LLMs and Generative AI, including prompt engineering, contextual reasoning, and knowledge retrieval.Hands-on experience developing Agentic AI systems and RAG pipelines for real-world enterprise applications.Strong programming skills in Python and solid understanding of data preprocessing, model development, and deployment lifecycles.Experience in end-to-end AI solution delivery, from experimentation and prototyping to production deployment and monitoring.Good understanding of data engineering principles, MLOps workflows, and vector-based search methodologies.Strong problem-solving mindset with the ability to communicate complex AI concepts to non-technical stakeholders.Experience working in cross-functional, agile environments, driving measurable business outcomes through AI adoption.

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

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: