Your AI career in the UAE starts here

We are looking for an experienced AI Development Engineer to join an exciting enterprise AI transformation project with a leading consulting organization.If you have hands-on experience building GenAI applications, RAG pipelines, AI agents and enterprise AI solutions, we would love to hear from you!Key Responsibilities:Develop GenAI applications, RAG pipelines, AI agents, copilots and automation workflows.Build responsive user interfaces using React, Next.js and TypeScript.Develop APIs, data connectors and AI integrations using Python and Azure AI services.Build PoCs, MVPs and reusable AI solutions for enterprise clients.Support AI testing, performance optimization, hallucination checks and responsible AI implementation.Required Skills & Experience:5–8 years of experience in software development, AI, cloud or automation.Strong hands-on experience with Python, FastAPI, React or Next.js.Experience with Azure OpenAI, Azure AI Foundry and Azure AI Search.Strong knowledge of RAG, embeddings, vector databases, prompt engineering and AI agents.Experience with APIs, Git, CI/CD, containers and automated testing.Good communication skills and experience working in Agile teams.All applications will be treated with strict confidentiality.

We have partnered with a leading consumer-focused business in the UAE to hire a Data Scientist. This is a role for someone who is genuinely curious about why people buy what they buy. The business sits on a rich and growing pool of customer data, and this person will turn that data into a real understanding of buyer behaviour, intent and emerging trends. The insight you produce will shape commercial decisions at the highest level, so if you want your work to actually move the needle rather than sit in a dashboard nobody opens, this is worth a look.This role suits a data scientist with strong commercial instincts who can bridge the gap between rigorous modelling and decisions the business can act on.About the role:Build models that decode buyer mentality, purchase intent and behavioural trends, turning raw customer data into insight the business can act onDevelop predictive and segmentation models that anticipate customer behaviour, identify emerging patterns and inform commercial strategyWork closely with commercial, marketing and product teams to frame the right questions and deliver answers that drive real decisionsTranslate complex analysis into clear, compelling narratives that resonate with non-technical stakeholders and senior leadershipDesign and run experiments that test hypotheses about customer behaviour and measure the impact of commercial decisionsContribute to the evolution of the data science function, bringing new techniques, tools and thinking into the team About you:5 years of experience in data science, with a track record of building models that have influenced real business decisionsStrong proficiency in Python and SQL, with hands-on experience across the full modelling lifecycle from exploration to deploymentSolid grounding in machine learning techniques including classification, clustering, regression and forecastingExperience working with customer, behavioural or transactional data to understand and predict buyer behaviourCommercially minded, with the ability to connect analysis directly to revenue, retention and growth outcomesStrong communicator who can turn technical work into insight that non-technical stakeholders understand and trustFinancial services or retail experience is strongly preferred

We're Hiring: Senior AI ResearcherLocation: United Arab Emirates (Remote)Employment Type: Full-TimeExperience Level: SeniorWork Arrangement: Fully RemoteAbout UsWe are a globally focused organization committed to advancing artificial intelligence research, intelligent technologies, and data-driven solutions that address complex business and operational challenges across diverse markets.Our multidisciplinary teams collaborate across Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Product, Research, Technology, Robotics, and Operations to translate advanced research into practical, scalable, and measurable applications.The RoleWe are seeking an experienced Senior AI Researcher to lead advanced research in artificial intelligence, machine learning, deep learning, generative AI, and emerging intelligent systems.The ideal candidate will combine strong theoretical foundations with practical research and engineering capabilities to investigate new methods, develop novel models and algorithms, conduct rigorous experiments, publish or document research findings, and translate promising research into production-oriented technologies.Key ResponsibilitiesLead advanced AI and machine-learning research projects from problem formulation through experimentation, validation, and technical delivery.Identify high-value research opportunities aligned with strategic, technological, and business priorities.Define research questions, hypotheses, methodologies, evaluation frameworks, and measurable objectives.Conduct literature reviews and monitor developments in artificial intelligence, machine learning, deep learning, and related fields.Analyze academic papers, technical publications, benchmarks, patents, open-source projects, and emerging research directions.Develop novel algorithms, models, architectures, and learning methodologies.Research improvements in model accuracy, efficiency, robustness, generalization, scalability, and interpretability.Investigate foundation models, large language models, multimodal AI, generative AI, reinforcement learning, computer vision, NLP, and other relevant AI areas.Design and conduct controlled experiments to evaluate new AI methods and hypotheses.Develop experimental protocols that support reproducible and statistically rigorous research.Build research prototypes and proof-of-concept systems to validate new concepts.Implement and test machine-learning algorithms using appropriate programming languages and frameworks.Develop training, validation, and testing pipelines for advanced AI models.Prepare and curate datasets for research and experimentation.Investigate data quality, distribution shifts, bias, imbalance, missing information, and other factors affecting model performance.Develop data augmentation, synthetic-data generation, sampling, and preprocessing strategies.Conduct model training, fine-tuning, transfer learning, and parameter optimization.Explore efficient training approaches including parameter-efficient fine-tuning, distillation, quantization, pruning, and other optimization methods.Develop and evaluate novel architectures and model components.Benchmark new approaches against established baselines and state-of-the-art methods.Design evaluation metrics and datasets appropriate to specific research problems.Perform ablation studies to understand the contribution of individual model components, features, datasets, and training techniques.Conduct statistical analysis of experimental results and assess the significance and reliability of findings.Perform robustness testing, sensitivity analysis, stress testing, and out-of-distribution evaluation.Investigate model failure modes, edge cases, hallucinations, biases, vulnerabilities, and unexpected behaviors.Develop methods to improve model reliability, interpretability, safety, and controllability.Research techniques for responsible AI, fairness, transparency, privacy, security, and model governance.Explore methods for evaluating large language models and generative AI systems, including factuality, reasoning, instruction following, groundedness, and safety.Research retrieval-augmented generation, agentic AI, tool use, knowledge integration, and intelligent decision-making systems.Investigate multimodal learning involving text, images, audio, video, structured data, and other information modalities.Research reinforcement-learning and optimization techniques for intelligent systems where appropriate.Explore techniques for efficient inference, model compression, hardware acceleration, and large-scale AI deployment.Develop scalable experimentation infrastructure in collaboration with Machine Learning and Software Engineering teams.Maintain reproducible research environments, experiment tracking, model repositories, datasets, and technical documentation.Develop automated experimentation, evaluation, benchmarking, and model-analysis workflows.Collaborate with engineering teams to transition validated research concepts into production systems.Assess the feasibility, scalability, computational requirements, and operational implications of research outcomes.Conduct technical feasibility studies for emerging AI technologies and research directions.Evaluate open-source and commercial AI models, platforms, frameworks, datasets, and infrastructure.Develop internal benchmarks and research datasets to measure AI-system performance.Establish research standards covering experimentation, reproducibility, documentation, evaluation, and data governance.Prepare technical reports, research papers, white papers, patents, internal research notes, and executive briefings.Present research findings to senior leadership, technical teams, research partners, and external audiences where appropriate.Contribute to academic publications, conferences, workshops, technical communities, or industry research initiatives where appropriate.Establish relationships with universities, research laboratories, technology companies, and external research organizations.Manage research collaborations, specialist consultants, external researchers, and technology partners where required.Mentor AI researchers, machine-learning engineers, data scientists, and junior technical professionals.Review research methodologies, experimental designs, technical papers, and model-development approaches.Provide technical leadership on complex AI research challenges.Identify opportunities to combine multiple AI techniques to address complex business and scientific problems.Monitor emerging AI capabilities and assess their potential practical applications.Develop research roadmaps, project plans, milestones, resource requirements, and technical priorities.Manage multiple research initiatives while maintaining scientific rigor and reproducibility.Provide leadership with regular updates on research progress, experimental results, technical risks, emerging technologies, and commercialization opportunities.Key Performance IndicatorsResearch project deliveryResearch milestone completionExperimental cycle timeResearch hypothesis validationModel performance improvementBenchmark performanceState-of-the-art comparisonExperiment reproducibilityExperimental success rateResearch prototype completionPrototype-to-production conversionModel accuracy and generalizationModel robustnessOut-of-distribution performanceInference efficiencyTraining efficiencyComputational cost optimizationDataset qualityEvaluation coverageBenchmark developmentAblation-study completionModel failure-rate reductionAI safety evaluation coverageResponsible-AI complianceResearch publication outputPatent and intellectual-property contributionTechnical documentation qualityResearch adoption by engineering teamsResearch-to-product conversionStakeholder satisfactionExternal research collaborationTechnology evaluation completionResearch roadmap executionKnowledge-sharing contributionMentoring and team developmentResearch infrastructure improvementExperiment automationModel monitoring and evaluation improvementInnovation contributionStrategic research impactIdeal CandidateThe successful candidate should have strong experience in artificial intelligence, machine learning, deep learning, computer science, computational research, generative AI, or a closely related research discipline, preferably within a technology company, research laboratory, university, advanced engineering organization, AI startup, or innovation-focused environment.The candidate should demonstrate:Deep understanding of artificial intelligence and modern machine-learning theory.Proven experience conducting original AI or machine-learning research.Strong knowledge of deep-learning architectures, optimization, representation learning, and statistical learning.Experience researching and developing advanced AI models and algorithms.Strong programming skills in Python and experience with modern AI frameworks such as PyTorch, TensorFlow, JAX, or equivalent technologies.Experience designing rigorous experiments and evaluating research hypotheses.Strong understanding of statistical analysis, experimental design, and model evaluation.Experience working with large-scale datasets and computationally intensive research environments.Strong knowledge of model training, fine-tuning, validation, benchmarking, and optimization.Experience with one or more advanced AI domains such as large language models, generative AI, computer vision, NLP, reinforcement learning, multimodal AI, or autonomous systems.Strong ability to analyze academic literature and identify meaningful research opportunities.Experience reproducing, extending, or improving published research.

BUSINESS INTRODUCTIONMajid Al Futtaim Holding is the leading shopping mall, retail, communities, entertainment developer and operator in the Middle East, North Africa, and Central Asia regions. With over 43,000 people, revenues of over US$ 11 Billion, and operations in 18 countries. Some of the iconic brands we carry include Mall of the Emirates, Carrefour, All Saints, Lego, City Center, Abercrombie & Fitch, & Vox Cinemas. We believe in making Great Moments for Everyone, Every day.JOB TITLEData Science Manage | MAF LifeStyle | LifestyleROLE SUMMARYThis role is the primary owner of demand forecasting, demand sensing, demand planning, and advanced customer segmentation capabilities – driving measurable commercial impact across a multi-brand, multi-market retail portfolio spanning UAE, KSA, Kuwait, Qatar, and Bahrain. The role partners closely with brand owners, buying and planning teamsROLE PROFILEOwn end‑to‑end demand forecasting across SKU, category, and brand levels (short, medium, long term), incorporating seasonality, promotions, sell‑through, and external market factors across GCC markets.Lead demand sensing initiatives using real‑time POS, digital, and macro signals to anticipate near‑term demand shifts and enable rapid commercial decisions.Partner with Buying & Planning teams to translate forecasts into OTB, replenishment, markdown optimization, and NPI strategies, presented in clear commercial language.Design advanced customer segmentation models (RFM, CLV, behavioral and propensity models) to enable personalized marketing, CRM, and loyalty activation.Identify and priorities high‑impact AI use cases across pricing, assortment, promotions, churn, store clustering, and next‑best‑action with quantified business value.Drive adoption of Computer Vision solutions including footfall analytics, shelf compliance, planogram adherence, visual search, and automated product tagging.Lead NLP and conversational AI initiatives such as chatbots, sentiment analysis, multilingual (Arabic/English) text analytics, and automated product content generation.Build and scale production‑grade ML solutions on Azure/Microsoft Fabric, including automated pipelines, monitoring, drift detection, and executive reporting via Power BI.REQUIREMENTSBachelor’s degree in STEM (Science, Technology, Engineering, Mathematics).Advanced degree in related topics is a strong plus.Background or previous experience in retail, fashion, or lifestyle industry is strongly preferred.Experience in GCC/MENA markets is an advantage.Strong customer segmentation & CLV modeling experience.WHAT WE OFFERAt Majid Al Futtaim, we’re on a mission to create great moments, to spread happiness, to build, experiences that stay in our memories for a lifetime. We’re proud to say that over the past 27 years, we have built a reputation as a regional market leader in what we do. Join us!Work in a friendly environment, where everyone shares positive vibes and excited about our future.Work with over 45,000 diverse and talented colleagues, all guided by our Leadership Model.

🚀 Hiring: Senior Data Scientist – Credit | FinTech | DubaiWe’re working with a fast-growing FinTech startup in Dubai that is looking to hire a Senior Data Scientist to join its expanding data team.This is a hands-on role with a strong focus on credit risk and credit modelling, so we’re specifically looking for candidates who have previously built and deployed models within a lending or credit environment.What we’re looking for:• 5+ years of experience in Data Science / Machine Learning• Strong experience within credit, lending or consumer finance• Proven experience building credit risk, credit scoring or underwriting models• Experience working with large-scale customer and transactional datasets• Strong Python and SQL skills• Experience taking models from development through to production• Comfortable working in a fast-paced FinTech/startup environment• Strong communication skills and ability to work closely with product, risk and engineering teams

Job DescriptionThe Agentic AI Developer will lead the translation of agentic research into production-grade components that enhance CRM automation and decisioning. The role requires ownership of end-to-end delivery: designing prototypes, validating behaviours against business metrics, and deploying resilient services that operate under real customer workloads. Success will be measured by increased automation coverage, demonstrable reductions in manual effort, and stable, auditable agent behaviour in production.Key ResponsibilitiesDesign and implement agentic AI features that automate CRM workflows and decision tasks.Develop reliable orchestration layers to coordinate multi-step agent actions and external integrations.Integrate multiple LLM providers and maintain model selection logic to meet latency and cost SLAs.Create evaluation suites and metrics to assess agent correctness, safety and long-term effectiveness.Build monitoring, alerting and runbooks to mitigate failures and unintended behaviours.Collaborate with product managers, platform engineers and support teams to prioritise use cases and measure business impact.Maintain development and testing infrastructure used for agent experimentation and deployment.RequirementsProven track record delivering AI or agentic prototypes into production systems.Substantial experience with Large Language Models and orchestration tooling; familiarity with major providers and fine-tuning techniques.Strong software engineering skills in Python, TypeScript or similar languages and experience building robust APIs and services.Practical experience creating evaluation frameworks, A/B tests and metrics-driven product iterations.Operational experience managing servers, CI/CD and deployment tooling for ML services.Excellent stakeholder communication with an ability to translate technical trade-offs into product decisions.