AI Jobs in Dubai

AI Engineer (LLM and RAG) - SCS AI SolutionsFull time · on site in Dubai · 12-month contract · immediate startThe AI engineer designs and builds the AI at the core of the solutions: document understanding, retrieval over policies and documents, classification and AI agents that work inside a client's business processes, with every output traceable and reviewable by a human.What you will doBuild retrieval-augmented generation (RAG) and agent solutions over Arabic and English business documents, policies and customer requests.Build extraction and classification pipelines for incoming documents (applications, reports, invoices, customer requests).Evaluate models for accuracy, hallucination, bias and Arabic quality; set up test sets and acceptance thresholds.Put guardrails in place: grounding with citations, human-in-the-loop review, prompt and model versioning, logging of every AI decision.Deploy on UAE-hosted services (Azure OpenAI in UAE regions or equivalent) and hand over to the client's team.Must haveSignificant experience in machine learning or AI engineering, with production LLM or RAG systems live with real users.Strong Python; experience with Azure OpenAI or Azure AI Foundry, vector search (Azure AI Search or similar) and an orchestration framework (Semantic Kernel, LangChain, LangGraph or similar).Document AI experience (Azure AI Document Intelligence or similar), including messy scanned PDFs.A structured way of evaluating LLM output (test sets, metrics, regression testing).Already present in the UAE and can start immediately (with 5 days notice).Nice to haveArabic language NLP; experience with Arabic models such as Jais.Microsoft certification AI-102 (Azure AI Engineer).Legal, policy or compliance document work.

About the Role:We are looking for an ambitious and adaptable AI Software Engineer to help build our trading-intelligence platform. The product is a website plus a Windows desktop app. The public site is the landing page. Users download the app and run the product on their own machine. You will work with the engineer who owns the platform, across the full stack, and turn business needs into working software.This is a product-engineering role. You will use modern LLM APIs inside a live trading product. We are hiring early-career engineers: strong graduates, or people with about one to two years of work.What you will work on:Web: A Next.js and React site, covering the public landing page and the signed-in product for pre-trade analysis, trade review, and chat.Backend: Python services for market analysis, user accounts, and live broker data.Chat: A trading assistant that answers questions, uses market and account context, and streams a clear written reply.Desktop: An Electron app, shipped as a Windows executable, that users download from the site and use as their main way into the product.Markets: MetaTrader 5 for prices, charts, and account history across forex, stocks, commodities, crypto, and indices.Infrastructure: The live system on AWS, deployed and looked after from the Linux command line.Key Responsibilities:Platform work: Improve the product wherever the work is: backend logic, the web app, the chatbot, or the desktop app.Backend: Build and maintain Python services for analysis, market data, authentication, and MT5.Chat: Help shape the assistant: how it understands a question, which tools it calls, and how it writes the answer.Desktop: Connect the desktop app to the backend, including authentication, updates, and safe use of model APIs.Trading integration: Integrate MT5 for prices, charts, account history, and position sizing. Treat live accounts with care, and change order flow only when that behaviour is explicitly in scope.Deployment: Help deploy and operate the stack on AWS EC2, including services, logs, and safe restarts.AI development tools: Use tools such as Cursor to move faster, and review what they produce before it ships.Collaboration: Work directly with the engineer who owns the platform and with the business. Explain trade-offs in plain language and ship small, testable changes.Experience:About one to two years in a software role, or a strong graduate with projects that stand in for that time. An internship counts.You have built something with a web frontend and a Python backend, at work, in an internship, or as a substantial project. You can read an existing codebase, follow how one service calls another, and make a small change without breaking the rest.You have called a hosted LLM from your own code. A course project, a side project, or a feature at work is enough. You know what a prompt, a tool call, and a streamed reply are, and you have seen a model answer badly and fixed the code around it.You are comfortable in a terminal. You do not need to have run production. You should be ready to deploy on a Linux server with someone who already knows the setup.A working interest in markets is enough. You should know what MT5 is, what a symbol and a timeframe are, and why account size matters for a trade. Brokerage experience is not required.Hard Skills & Qualifications:Architecture: You can look at a small system and explain where data lives, which part talks to the outside world, and what the website and the desktop app each do.Backend: Solid Python. Familiar with FastAPI, async code, Postgres, and Redis, from work or from projects you can talk through.Frontend: Hands-on React and Next.js with TypeScript. Familiar with Tailwind. You can build a screen and match an existing design.Desktop: You have used Electron, or a similar desktop stack, and you can learn how we package the Windows app.AI integration: You have used a hosted model API such as OpenAI, Gemini, or OpenRouter. You can change a chatbot’s behaviour in code, not only by rewriting a prompt.Markets: A basic grasp of forex, indices, commodities, and crypto, plus the idea of risk per trade. You understand why a trading assistant must not invent prices or place trades by accident.AWS and Linux: You can use the Linux command line. You have some exposure to cloud servers, or you can get comfortable on EC2 quickly with guidance.AI tools: You already use coding assistants in daily work, and you read the change before you keep it.Communication: You can explain a technical choice to someone who is not an engineer, and you can turn a business request into a small piece of working software.Nice-to-Haves:A small Electron app you can show.A chatbot that calls tools, even as a project.A deploy you did yourself, on any Linux host.Personal trading, a markets elective, or time around a broker platform.How the role works:You will pair with the engineer who already owns the platform. Expect to pick up a slice of work, such as a chatbot change, an analysis fix, a desktop update, or a screen in the app, and carry it through with review. You will learn the trading domain and the production setup on the job. Judgment still matters. Trading users act on what the product says..

Company Description KON-ae is a next-generation AI Agent digital human workspace that enables enterprises to deploy real-time agentic AI avatars capable of performing tasks and collaborating with human teams. The company focuses on replacing fragmented tools and static automation with intelligent, always-on AI agents that communicate, act, and execute tasks through human-like avatar interfaces. KON-ae helps organizations eliminate operational friction, unlock contextual intelligence, and scale productivity without increasing headcount. Growing teams rely on KON-ae for AI agentic avatars, digital twin technology, customer support automation, internal query handling, knowledge base intelligence, and custom AI solutions. Founded in 2024 and based in Dubai, United Arab Emirates, KON-ae partners with forward-thinking enterprises to reimagine how work gets done through deeply integrated, interactive AI agents.Role Description The AI Engineer will design, build, and optimize AI agents and digital human avatars that integrate seamlessly into enterprise workflows. This full-time, on-site role in Dubai, United Arab Emirates involves developing and deploying machine learning models, including neural networks and NLP systems, to power real-time interactions and task execution across departments. The AI Engineer will collaborate with product, design, and engineering teams to translate business requirements into scalable AI solutions, implement APIs and integrations, and ensure robust performance in production environments. Day-to-day responsibilities include data analysis and pattern recognition, model training and evaluation, software development and testing, and continuous improvement of agent behavior and contextual intelligence. The role also includes documenting technical approaches, contributing to architecture decisions, and supporting enterprise customers during implementation and optimization phases.Qualifications Strong foundation in Computer Science and Software Development, including algorithms, data structures, and modern programming languages (e.g., Python, JavaScript, or Java).Hands-on experience with Neural Networks and Pattern Recognition, using frameworks such as TensorFlow, PyTorch, or similar deep learning libraries.Practical expertise in Natural Language Processing (NLP), including building, fine-tuning, and deploying language models for real-time conversational agents.Experience designing and deploying AI solutions in production environments, including RESTful APIs, microservices, and cloud platforms (e.g., AWS, GCP, Azure).Knowledge of data pipelines, model evaluation, and monitoring, with a focus on reliability, scalability, and low-latency inference.Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience.Ability to work closely with cross-functional teams, communicate complex technical concepts clearly, and

Join one of the world's leading multi-strategy investment platforms as a Quant Researcher focused on Machine Learning and AI. This role sits within a highly successful systematic investment team that is investing heavily in next-generation research capabilities and the application of cutting-edge machine learning techniques to financial markets.The team is seeking exceptional researchers who can bring expertise from frontier AI, deep learning, large-scale modelling, and modern machine learning research into a fast-paced environment where ideas are rapidly tested and deployed. This is an opportunity to work on some of the most challenging prediction problems in the world while having direct impact on investment performance.ResponsibilitiesDevelop and implement machine learning models to identify predictive signals across global marketsResearch and apply state-of-the-art deep learning techniques for alpha generationDesign and test neural network architectures for financial forecasting and pattern recognitionWork with large, complex, and alternative datasets to uncover unique sources of investment insightConduct rigorous research, experimentation, and statistical validation of trading signalsCollaborate closely with Portfolio Managers, Quant Researchers, and Data ScientistsBuild scalable research infrastructure and production-ready modelling pipelinesStay at the forefront of developments in AI, machine learning, and quantitative researchContribute to the development of systematic investment strategies using modern ML techniquesRequirementsPhD or Master's degree in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative disciplineStrong background in machine learning research and modellingExperience building and deploying deep learning models in real-world environmentsExpertise in areas such as neural networks, representation learning, transformers, foundation models, reinforcement learning, probabilistic modelling, or large-scale optimisationExcellent programming skills in Python and familiarity with modern ML frameworks such as PyTorch or TensorFlowStrong mathematical and statistical foundationsDemonstrated ability to conduct independent research and solve complex problemsExperience from leading AI labs, deep technology companies, research institutions, or high-performance machine learning environments is highly desirablePreferred BackgroundsWe are particularly interested in candidates from:Leading AI research labsFrontier foundation model teamsDeep learning and applied AI organisationsResearch-focused technology companiesQuantitative research groupsHigh-performance computing and data science environmentsAcademic researchers with strong publication records in machine learning or artificial intelligenceWhat You'll GetOpportunity to apply cutting-edge AI research to real-world investment decisionsAccess to significant computational, data, and research resourcesHighly collaborative environment alongside world-class investors and researchersCompetitive compensation package with substantial upside potentialDirect impact on investment outcomes and business growthRelocation support to Dubai where applicableExposure to one of the most intellectually challenging applications of machine learningThis position is ideal for researchers who are passionate about solving difficult prediction problems, building innovative machine learning systems, and applying frontier AI techniques in a highly competitive and rewarding environment. Desired Skills and ExperienceSeeking elite ML Researchers and PhDs to develop deep learning models for alpha generation within a highly capitalised, technology-driven investment team.

Job title: Machine Learning Engineer 1Location: Dubai, UAEAbout noonWe’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a (add title) who can help us move even faster.noon’s mission: Every door, every day.What you'll do:Team noon has some of the fastest, smartest, and hardest-working people we've encountered. As a Machine Learning Engineer (MLE1), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantagesDeeply engage in the technical work: building, training, and deploying production-grade models across our domainsContribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detectionPartner with the broader engineering team to implement optimal deployment strategies for heavy ML workloadsAdhere to and contribute to the standardization of ML Ops and best practices within the teamWhat you'll need:Experience: hands-on experience or relevant internships in Machine Learning or data science is preferredFoundational Knowledge: Strong academic or practical grounding in core machine learning concepts, statistics, and data structuresCoding & Frameworks: Proficiency in Python and familiarity with standard ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn) and SQLGrowth & Collaboration: Eagerness to learn from senior engineers, collaborate across product and engineering teams, and rapidly ramp up on MLOps best practicesTech Stack: Basic exposure to cloud platforms (like GCP) and data processing pipelines.

About the roleAs a Forward Deployed Engineer (FDE) at Albatha Group, you embed with our internal customers to turn AI from a promising demo into a production system that moves their business. You will own the full arc: understand the customer's problem, design and build LLM-powered solutions, deploy them into messy real-world environments, and feed what you learn back into our product.This role suits engineers who like being close to the problem, can write production-grade code, and are equally comfortable in a whiteboard session with a C level and a debugging session with a data team.What you'll doEmbed with customer teams to understand their workflows, data, and constraints, and identify where AI can deliver measurable value.Scope and prioritize use cases with technical and business stakeholders, turning ambiguous problems into clear delivery plans.Design and build production AI solutions: LLM-based agents, retrieval-augmented generation (RAG), tool/function calling, document processing, and workflow automation.Integrate with customer systems such as data warehouses, CRMs, ticketing tools, internal APIs, and legacy software.Build evaluation harnesses and monitoring so quality, latency, cost, and safety are measured, not guessed.Deploy and operate solutions in customer environments, including cloud, VPC, and on-prem setups with security and compliance requirements.Iterate with end users after launch, tuning prompts, retrieval, models, and UX based on real usage.Turn repeated customer needs into reusable components, and bring product and research teams concrete feedback from the field.Present results, trade-offs, and roadmaps to executives and engineers alike.What you'll bring4+ years of software engineering experience, with strong Python and working fluency in TypeScript or a similar language.Hands-on experience shipping LLM applications to production: prompt design, RAG, agents, tool use, structured outputs, and fine-tuning where it fits.Practical knowledge of evaluating AI systems, including building test sets, using LLM-as-judge methods, and tracking regressions.Experience with vector search, embeddings, and data pipelines, plus solid SQL and API integration skills.Comfort with cloud infrastructure (AWS, GCP, or Azure), containers, and CI/CD.Clear communication with both technical and non-technical audiences, including the ability to run workshops and explain trade-offs plainly.A bias for ownership: you take a problem from vague request to deployed, working solution.Willingness to travel to customer sites as needed (see logistics below).Nice to havePrior experience in a forward deployed, solutions engineering, consulting, or startup founding role.Experience with agent frameworks, Model Context Protocol (MCP), or multi-agent orchestration.Background in a regulated industry such as finance, healthcare, or government, including security reviews and data governance.Familiarity with model serving, inference optimization, or open-weight model deployment.Experience with front-end work to build quick internal tools and prototypes for customers.Contributions to open-source AI tooling or published technical writing.

About the roleAs an AI Engineer at Albatha Group, you embed with our customers to turn AI from a promising demo into a production system that moves their business. You will own the full arc: understand the customer's problem, design and build LLM-powered solutions, deploy them into messy real-world environments, and feed what you learn back into our product.This role suits engineers who like being close to the problem, can write production-grade code, and are equally comfortable in a whiteboard session with a VP and a debugging session with a data team.What you'll doEmbed with customer teams to understand their workflows, data, and constraints, and identify where AI can deliver measurable value.Scope and prioritize use cases with technical and business stakeholders, turning ambiguous problems into clear delivery plans.Design and build production AI solutions: LLM-based agents, retrieval-augmented generation (RAG), tool/function calling, document processing, and workflow automation.Integrate with customer systems such as data warehouses, CRMs, ticketing tools, internal APIs, and legacy software.Build evaluation harnesses and monitoring so quality, latency, cost, and safety are measured, not guessed.Deploy and operate solutions in customer environments, including cloud, VPC, and on-prem setups with security and compliance requirements.Iterate with end users after launch, tuning prompts, retrieval, models, and UX based on real usage.Turn repeated customer needs into reusable components, and bring product and research teams concrete feedback from the field.Present results, trade-offs, and roadmaps to executives and engineers alike.What you'll bring5+ years of AI experience, with strong Python and working fluency in TypeScript or a similar language.Hands-on experience shipping LLM applications to production: prompt design, RAG, agents, tool use, structured outputs, and fine-tuning where it fits.Practical knowledge of evaluating AI systems, including building test sets, using LLM-as-judge methods, and tracking regressions.Experience with vector search, embeddings, and data pipelines, plus solid SQL and API integration skills.Comfort with cloud infrastructure (AWS, GCP, or Azure), containers, and CI/CD.Clear communication with both technical and non-technical audiences, including the ability to run workshops and explain trade-offs plainly.A bias for ownership: you take a problem from vague request to deployed, working solution.Willingness to travel to customer sites as needed (see logistics below).Nice to havePrior experience in a forward deployed, solutions engineering, consulting, or startup founding role.Experience with agent frameworks, Model Context Protocol (MCP), or multi-agent orchestration.Background in a regulated industry such as finance, healthcare, or government, including security reviews and data governance.Familiarity with model serving, inference optimization, or open-weight model deployment.Experience with front-end work to build quick internal tools and prototypes for customers.Contributions to open-source AI tooling or published technical writing.

Job Title – Azure AI Foundry DeveloperCompany – TCS (MEA)Location – UAEJob type – Full timeAbout Us:Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world’s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile™ delivery model, recognized as a benchmark of excellence in software development.A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world’s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.Job Description:Looking for an Azure AI Foundry Developer with hands-on experience in developing and deploying enterprise Generative AI solutions.Key Skills:Azure AI Foundry & Azure OpenAIGenAI, LLMs & Agentic AIRAG, embeddings & Azure AI SearchPrompt engineering & model integrationPython, FastAPI & REST APIsAI agents and orchestration frameworksAzure services, Key Vault & Entra IDGit, CI/CD & production deploymentLLM evaluation, monitoring & optimizationUnderstanding of Responsible AI and security practicesExperience: Preferably 5+ years overall, with strong hands-on Azure/Python development and recent GenAI implementation experience.Preferred: Experience delivering AI solutions in Banking/Financial Services or regulated environments.Application Deadline: 7th-Nov-2026Privacy Note:https://www.tcs.com/connect-with-tcs/privacy-policy

Position: Senior LLMOps / AI Platform EngineerLocation: DubaiIndustry: Financial ServicesSalary: AED 25 - 30K/ monthRole Overview:The job holder will be responsible for building, deploying, optimizing, and operating production-grade LLM and Generative AI infrastructure. The role combines LLM inference, GPU optimization, Kubernetes, cloud infrastructure, observability, RAG, and AI platform engineering.Responsibilities:Deploy and operate self-hosted LLMs using vLLM, SGLang, Ollama.Optimize LLM inference for latency, throughput, concurrency, GPU memory, KV cache, and cost.Manage GPU workloads across multiple NVIDIA GPUs.Deploy and maintain AI services on Kubernetes / AWS EKS using Docker and Helm.Implement LLM reliability mechanisms including health checks, monitoring, automated recovery, and model restart/refresh strategies.Implement observability using Langfuse/LangSmith, OpenTelemetry, Prometheus, and Grafana.Deploy and optimize RAG systems, embedding models, and vector databases such as Qdrant, Milvus.Support AI agents and workflows built with LangChain and LangGraph.Build and maintain CI/CD pipelines for AI services and infrastructure.Troubleshoot production issues across LLMs, GPUs, Kubernetes, networking, and AI applications.Requirements:Strong Python and FastAPI experiencevLLM, Hugging Face and self-hosted LLM deploymentKubernetes, Docker, Helm and AWSNVIDIA GPU inference and performance optimizationLangChain / LangGraph/LangSmithRAG, embeddings and vector databases (Qdrant)LLM observability and monitoringPostgreSQL / Redis  GitHub Actions / CI/CDStrong production troubleshooting skillsEmail CVs to: mahin@hirerightt.com

Be part of shaping how AI transforms how we work. You'll scout emerging AI technologies, pilot new tools, and coordinate cross-departmental adoption projects. A key focus will be managing and enhancing our internal Knowledge Hub — ensuring information flows seamlessly and employees can leverage AI to its fullest.Design and implement agentic architectures — multi-step planners, ReAct loops, tool-use orchestration, and memory systemsBuild reliable agent pipelines that handle ambiguity, recover from failures, and know when to escalate to humans Integrate LLMs (Claude, GPT, open-source models) with external tools, APIs, databases, and enterprise systemsDevelop evaluation frameworks to measure agent reliability, accuracy, cost, and latency in productionImplement guardrails, safety layers, and human-in-the-loop controls for autonomous systemsOptimize for real-world constraints: token costs, latency budgets, rate limits, and context window managementCollaborate with product and engineering teams to identify high-value automation opportunities across the digital entertainment portfolioContribute to internal tooling and frameworks that accelerate agent development across the organizationRequirements5+ years of software engineering experience, with at least 1-2 years focused on LLM-based systems Hands-on experience building agentic systems — not just prompt engineering, but orchestration, tool use, and state management Strong proficiency in Python; familiarity with TypeScript is a plus Deep understanding of LLM APIs (Claude, OpenAI, etc.), including function calling, structured outputs, and streaming Experience with at least one agent framework (LangGraph, CrewAI, AutoGen, custom frameworks)Solid software engineering fundamentals: testing, CI/CD, observability, version controlExperience with RAG pipelines, vector databases (Pinecone, Weaviate, pgvector), and retrieval systemsExperience with MCP (Model Context Protocol) or similar tool-integration standards

Role purposeBuild generative AI applications and agent-based workflows that support employees and improve brokerage operations. Develop reliable retrieval, reasoning and tool-use capabilities around approved company knowledge and data. Turn use cases such as support assistance, policy search and operational investigation into tested, observable and maintainable software.Key responsibilitiesAI application developmentDevelop Python services and APIs for internal assistants, client-support copilots, document processing, case summarisation and operational analysis.Build retrieval-augmented generation pipelines using approved policies, procedures, product specifications and knowledge content, with source attribution and document version awareness.Implement agent workflows with structured outputs, tool schemas, bounded execution, state management, approval checkpoints and clear termination conditions.Develop brokerage-specific responses that respect entity, product, language and client context; prevent unsupported claims about trading conditions or account status.Quality and model optimisationCompare model and retrieval approaches using representative datasets; select configurations based on grounded accuracy, task completion, latency and operating cost.Improve chunking, embeddings, metadata filters, reranking and context construction while preserving source permissions and preventing cross-client information leakage.Maintain versioned prompts, model configurations and evaluation datasets; use fine-tuning only where a validated business case and suitable approved data exist.Work with QA to test hallucinations, prompt injection, sensitive information disclosure, ambiguous instructions and failure to request human assistance.Production delivery and supportIntegrate approved enterprise tools through controlled interfaces, using authenticated user context and explicit authorisation for actions that modify records or trigger workflows.Instrument application traces, retrieval results, model usage and tool outcomes with appropriate redaction, enabling diagnosis without exposing unnecessary client information.Implement graceful failure, timeouts, retries and human handoff when information is missing, confidence is insufficient or a requested action exceeds permissions.Maintain code, tests and operational documentation; investigate production failures and use reviewed feedback to improve application performance over time.Essential experience and qualifications4+ years in software, data or ML engineering, including at least 2 years building applied NLP, generative AI or LLM-based systems.Evidence of shipping and supporting production AI applications, including retrieval or agent workflows; prompt-only experimentation is insufficient.Strong Python, API development, automated testing, Git and software design skills.Hands-on experience with LLM APIs or open-weight models, embeddings, vector or hybrid search, structured outputs and tool calling.Understanding of evaluation design, retrieval quality, prompt injection risks, context limitations and the variability of model outputs.Ability to work with SQL, enterprise documents and permission-controlled data and to explain application limitations to business stakeholders.Bachelor’s degree in Computer Science, AI, Engineering or a related field, or equivalent practical experience.Preferred experienceFinancial services experience, particularly brokerage operations, trading support or client service.Experience with an agent orchestration framework, multilingual retrieval and document extraction or OCR.Experience with model adaptation, inference optimisation and observability for LLM applications.

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.

We are looking for an AI Platform Operations Lead to take full ownership of our client's multi-cloud AI ecosystem. In this role, you’ll sit at the absolute bleeding edge of technology—architecting multi-agent orchestrations, scaling Voice AI, operationalizing Model Context Protocol (MCP), and running high-performance LLMOps across Azure OpenAI, AWS Bedrock, and Core42 Compass.What You’ll DoAgentic AI & MCP: Scale complex multi-agent orchestrations using LangGraph & Microsoft Agent Framework while operationalizing Model Context Protocol (MCP) integrations.LLMOps & Observability: Optimize PTU capacity, latency, token spend, and monitoring via Comet Opik, Azure Monitor, and AWS CloudWatch.Cloud & Voice Infrastructure: Manage AKS, Docker, APIM, and IaC (Terraform/Bicep) alongside cutting-edge Voice AI (ElevenLabs).Governance & Security: Enforce Responsible AI guardrails, content filtering, Entra ID RBAC, and zero-trust security.What We’re Looking ForDeep expertise in Azure AI, AWS Bedrock, Kubernetes, and Python.Proven track record in LLMOps, agentic workflows, and cloud-native automation.What's on offer?Competitive monthly salaryTax-free compensation package in DubaiVisa sponsorship and comprehensive benefitsHigh-visibility role shaping multi-market strategic initiatives

AI Engineer - DubaiDiscover the Opportunity:We're partnering with an innovative technology organisation that is investing heavily in AI to build next-generation software solutions for enterprise customers.As the business continues to expand its AI capability, they're looking for an AI Engineer to design, develop, and deploy production-ready AI solutions that solve complex business challenges.This is a highly hands-on engineering role where you'll take ownership of AI features throughout the full software development lifecycle, working alongside product and engineering teams to deliver scalable, reliable, and commercially impactful solutions.Discover the Responsibilities:Design, develop, and deploy production-grade AI applications using modern machine learning and Generative AI technologiesBuild scalable AI solutions leveraging LLMs, RAG architectures, and agentic AI frameworks to solve real-world business challengesCollaborate with product and engineering teams to translate business requirements into robust, production-ready solutionsDrive technical decision-making, optimise AI systems based on production performance, and promote engineering best practices across the teamDiscover the Requirements:7+ years of software engineering experience, including significant hands-on experience delivering AI solutions into productionProven track record of building AI-powered products that have been successfully launched and are actively used by customers in live environmentsStrong expertise in Python, Generative AI, Large Language Models (LLMs), prompt engineering, RAG architectures, and modern AI frameworks such as LangChain or similarExperience building scalable backend services, APIs, and distributed applications using modern software engineering practicesStrong understanding of cloud platforms, containerisation, CI/CD, MLOps, and deploying AI applications at scaleExperience working with SQL/NoSQL databases, ETL pipelines, and large-scale data processingExcellent communication skills with the ability to work across product, engineering, and business stakeholdersA proactive, product-focused mindset with experience working in fast-paced engineering environments and a passion for building AI solutions that deliver real commercial impact

📍 On-site in Dubai💰 AED 30,000 - 35,000About the CompanyWe're partnering with a forward-thinking organisation that's going beyond simply adopting AI, they're building it into the way their entire business operates.With AI systems already running in production, they're investing in the next generation of intelligent technology, from autonomous AI agents and advanced retrieval systems to self-hosted LLMs.And this is where things get exciting. You'll be joining a small engineering team with big ambitions, where your ideas won't get lost in layers of approval. You'll have the opportunity to influence technical decisions, experiment with emerging technologies and build AI solutions that make a real difference across the business.ResponsibilitiesBuild and maintain production AI systems using Python, developing backend services and intelligent applications.Develop AI agents and automated workflows, including LLM integrations, tool calling, routing and orchestration.Design and improve RAG and GraphRAG systems, working with knowledge graphs, vector databases and semantic search.Build AI evaluation frameworks to measure retrieval quality, agent performance and reliability.Benchmark open-source LLMs and contribute to the transition towards self-hosted model infrastructure.Improve system reliability through monitoring, observability, automated testing and production support.Collaborate with engineering and business teams to translate operational challenges into practical AI solutions.Take ownership of development from initial design through to deployment and ongoing improvement.Qualifications4+ years of experience developing AI applications or working in AI/software engineering roles involving production AI systems.Strong hands-on experience with Python and backend development.Hands-on experience building AI-powered applications using LLMs, with exposure to technologies such as RAG, AI agents or tool calling.Understanding of REST APIs and integrating AI capabilities into existing applications.Familiarity with vector databases, semantic search or retrieval-based systems.Comfortable working with other engineers, reviewing code and contributing to production applications.A proactive approach to problem-solving and an interest in learning new AI technologies.Preferred SkillsExperience in any of the following would be beneficial, but you don't need to have worked with all of them:GraphRAG, knowledge graphs or ontologies.LLM evaluation, retrieval metrics and regression testing.PyTorch, Hugging Face, Ollama or vLLM.Qdrant, Milvus or other vector databases.Docker, Kubernetes or model-serving infrastructure.Apply with your CV, or get in touch to learn more about the company, the projects and what they're looking to build!

ML engineerLocation: DubaiDuration: 12 monthsVisa : Work Permit, Dependent, Tourist Visa. Need Someone in Dubai only. Position SummaryAs an ML Engineer (MLOps), you will take machine-learning models and AI pipelines from proof-of-concept through to scalable, reliable production deployment. You will own deployment, monitoring, and optimization across both edge and cloud environments.Responsibilities• Deployment: Deploy ML models and AI pipelines from PoC / development to production, ensuring they scale efficiently and maintain high performance through seamless CI/CD integration and orchestration.• Monitoring & Maintenance: Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.• Model Optimisation & Pruning: Optimise models for inference speed and resource efficiency using techniques such as quantisation, pruning, and knowledge distillation for edge and cloud deployment.• Data Preprocessing: Perform data collection, cleaning, and feature engineering to prepare datasets for training.• Model Training & Tuning: Implement continuous / semi-continuous training and evaluation workflows to maintain accuracy over time, and fine-tune models for optimal performance.• Collaboration: Work with data scientists, software engineers, DevOps, and product managers to understand requirements and deliver ML solutions.• Documentation: Maintain clear, organised documentation of code, models, and processes.Qualifications• Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, AI, or a related field.• 5 – 9 years of relevant experience.• Proficiency in Python and libraries such as PyTorch, NumPy, Pandas, and Scikit-learn.• Knowledge of model deployment, containerisation, and orchestration (Docker, Kubernetes).• Knowledge of SQL and NoSQL databases.• Familiarity with one or more cloud platforms (AWS, GCP, or Azure).• Familiarity with MLOps tools such as MLflow, ClearML, Azure ML, or AWS SageMaker.• Strong understanding of deep learning, reinforcement learning, and other ML techniques.Preferred Qualifications• Experience deploying computer-vision models to edge devices or low-resource environments.• Familiarity with infrastructure-as-code tools and observability platforms.• Contributions to open-source computer-vision projects or relevant publications.Core Technical Skills• Languages: Python.• Frameworks & Libraries: PyTorch, TensorFlow, OpenCV, Scikit-learn, Pandas, NumPy, FastAPI.• Serving ; Deployment: Docker, Kubernetes, GitLab CI (CI/CD).• Databases: PostgreSQL, MySQL, MongoDB, Elasticsearch, Neo4j.• Deep-Learning Architectures: CNN, LSTM, GAN, Transformers, LLM.• MLOps & Distributed Computing: MLflow, Kubeflow, Ray, ClearML.• Message Brokers & GPU: RabbitMQ, Kafka; CUDA, RAPIDS, Numba.• Cloud Platforms: AWS, Azure, GCP.

Job Title – Azure AI Foundry ArchitectCompany – TCS (MEA)Location – Dubai, UAEJob type – Full timeAbout Us:Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world’s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile™ delivery model, recognized as a benchmark of excellence in software development.A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world’s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.Key ResponsibilitiesAzure AI Foundry & Azure OpenAIGenerative AI, LLMs & Agentic AIRAG, embeddings & Azure AI SearchPrompt engineering & model evaluationPython, REST APIs & enterprise integrationsAzure security, Entra ID, Key Vault & RBACMLOps/LLMOps, CI/CD & production deploymentResponsible AI, governance & monitoringStrong solution architecture & stakeholder communication with strong Azure architecture and recent hands-on GenAI experience.Preferred: Experience delivering AI solutions in Banking/Financial Services or other regulated environments.Application Deadline: 30th -October -2026Privacy Note:https://www.tcs.com/connect-with-tcs/privacy-policy

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 Senior Manager AI Software Engineering at the corporate office, reporting to the Associate Director Software Engineering. The job holder is responsible for designing, building, 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.Key Responsibilities:AI Agent Development on Microsoft FoundryDesign, build, and deploy pro-code AI agents on Microsoft Foundry, leveraging its agent framework, model catalogue, and tool/function-calling capabilities.Integrate agents with Palantir Foundry via MCP (Model Context Protocol) to fetch enterprise data and execute Ontology actions, alongside other tool, retrieval, memory, and multi-agent orchestration patterns in Python.Build evaluation harnesses and guardrails (groundedness, safety, cost, latency) and iterate on prompts, tools, and architectures based on measured outcomes.LLM Engineering & ProductionizationApply prompt engineering, structured output, RAG, and grounding techniques appropriate to each use case.Operate agents in production: observability, tracing, cost monitoring, regression testing, and incident response.Manage versioning of prompts, tools, and agent configurations alongside code.Azure & Platform IntegrationIntegrate with Azure services (Azure OpenAI, AI Search, Storage, Functions, Container Apps, Key Vault, Entra ID) to deliver secure, scalable agent solutions.Build and maintain CI/CD pipelines for agent deployment, including automated evals as a release gate.Implement authentication, authorization, secret management, and data-handling patterns aligned with enterprise security standards.Cross-functional CollaborationWork closely with Product Managers, Data Scientists, and IT Architects to translate agent use cases into delivery plans.Communicate trade-offs (model choice, latency, cost, accuracy) clearly to technical and non-technical stakeholders.Champion agentic patterns and reusable components across the engineering organization.Who we are looking for:Software engineering experience with 2+ years of hands-on experience building AI agents and production-grade LLM-based/agentic systems, including tool use, orchestration, RAG, evaluations (evals), and multi-agent workflows.Education / Professional Certifications:Bachelor’s degree in computer science, Engineering, or related quantitative fieldAdvanced degrees preferred.Technical 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 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 plusBehavioural CompetenciesHigh-energy, ownership-driven mindsetStrong problem-solving and analytical skillsExcellent communication and collaboration abilitiesComfortable navigating ambiguity and driving clarityExperience in agile/start-up environments preferred Track record of taking AI/ML or agent projects from prototype to productionAs 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.

We are HIRING!!!! Looking for an experienced Edge AI Engineer (AI Product Consultant) to design, develop, and deploy AI-powered solutions that operate on edge devices and integrate with digital products and enterprise platforms.Responsibilities:AI Product Development: Work with Product Managers and stakeholders to identify AI opportunities, understand business needs, and develop practical AI solutions.Edge AI Engineering: Design, develop, and deploy AI/ML models on edge devices, focusing on real-time performance, computer vision, and IoT technologies.AI Integration: Integrate AI solutions with applications, APIs, cloud platforms, and enterprise systems, ensuring scalability, security, and reliability.Product Delivery: Manage AI solutions from proof of concept (PoC) to production deployment, collaborating with engineering and product teams.Technical Consulting: Provide technical recommendations, assess feasibility, communicate with stakeholders, and continuously improve AI product performance.Skills5+ years of relevant software engineering, AI/ML engineering, or solution development experience.Strong programming skills in Python and preferably C++.Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow.Experience deploying and optimizing AI models on edge devices.Knowledge of computer vision, real-time inference, and model optimization.Familiarity with NVIDIA Jetson, TensorRT, ONNX, or similar edge AI technologies.Experience with REST APIs, IoT integration, and cloud platforms.Understanding of AI product development, architecture, and technical feasibility assessment.Strong problem-solving, consulting, communication, and stakeholder management skills.Reach out to trish.villena@globant.com for discussion!!

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 Overview:As the Lead Agentic AI Engineer within the Enterprise Data Platform (EDP) at MultiBank Group, you will define and build MBG’s agentic AI capability. The EDP provides the governed data foundation for analytics, machine learning, and AI across the Group, and MBG has launched a Group-wide initiative to design and deploy AI agents for Sales, Marketing, Finance, Operations, Customer Service, and Compliance.You will own the end-to-end lifecycle of AI agents, from use-case discovery with business teams through architecture, development, evaluation, deployment, and production monitoring. You will set the technical direction, standards, and reference architecture for agent development at MBG while remaining hands-on, and you will lead and mentor AI engineers. You will work closely with data engineers, platform and security teams, and business leaders, reporting directly to the Head of Data & AI.Key ResponsibilitiesAgentic AI Design & DevelopmentDesign, build, and deploy single- and multi-agent systems that automate workflows and decision support across Sales, Marketing, Finance, Operations, and other business domains.Implement agent patterns including tool use, planning, memory, retrieval-augmented generation (RAG), and multi-agent orchestration.Build integrations to enterprise systems (EDW/Redshift, CRM, Back Office, payments, support, and marketing platforms) using APIs and Model Context Protocol (MCP) servers.Partner with business stakeholders to identify high-value use cases, define success metrics, and convert them into production agents.Evaluation, Reliability & SafetyEstablish evaluation frameworks for agents covering task success, accuracy and groundedness, regression testing, and cost and latency benchmarks.Implement guardrails, human-in-the-loop checkpoints, permission scoping, and fallback behavior for sensitive financial and compliance workflows.Monitor agents in production for quality, drift, hallucination, failure modes, and misuse, and drive continuous improvement.Cloud AI Platform EngineeringBuild and operate agent and LLM workloads on AWS (Bedrock, Bedrock Agents/AgentCore, Lambda, ECS/EKS, Step Functions, SageMaker where appropriate).Evaluate and integrate foundation models (Claude, OpenAI, and open-source) with attention to quality, cost, and data-residency requirements.Collaborate with platform and security teams on scalability, identity and access, secrets management, observability, and cost control (FinOps for LLM usage).LLMOps & Engineering ExcellenceImplement CI/CD, versioning for prompts, tools, and agent configurations, automated testing, and release practices for agent systems.Build reusable components, SDKs, and templates so business-aligned teams can build agents consistently and safely.Ensure production-quality code, documentation, and runbooks.Data CollaborationWork with data engineers to consume curated EDW datasets and to expose governed data and semantic layers (e.g., business glossary, metadata) to agents.Define retrieval and knowledge strategies (vector stores, structured query tools, text-to-SQL with guardrails) aligned with enterprise data models and governance standards.AI Governance, Security & ComplianceEnsure agents comply with MBG’s AI governance policy, data classification rules, and regulatory requirements, keeping PII and sensitive trading data within approved boundaries.Provide auditability, traceability (prompt, tool-call, and decision logs), and explainability for agent actions.Contribute to the AI Governance Committee’s standards and approval processes.Technical LeadershipLead, mentor, and grow AI engineers; run design and code reviews.Define the agentic AI roadmap, reference architectures, and engineering standards with the Head of Data & AI.Communicate trade-offs and results clearly to senior and non-technical stakeholders.Continuously evaluate emerging models, frameworks, and agent tooling.Qualifications & RequirementsExperience & Education8+ years of experience in software engineering, ML, or AI engineering, including 2+ years building LLM/agentic systems with at least one delivered to production.Experience leading or mentoring engineers; technical lead experience preferred.Bachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.Master’s degree or relevant certifications (AWS ML Specialty, AWS AI Practitioner/Developer, other AI certifications) are a plus.Agentic AI & LLM EngineeringProven experience building and deploying LLM-based agents in production (tool/function calling, orchestration, RAG, memory, multi-agent workflows).Hands-on with agent frameworks and protocols such as LangGraph, LangChain, LlamaIndex, Strands, or the Claude/OpenAI agent SDKs, and MCP.Strong prompt and context engineering skills, and experience with LLM evaluation (offline evals, LLM-as-judge, human review) and observability tooling.Understanding of guardrails, prompt-injection risks, and safe tool-permission design.AWS & CloudStrong hands-on experience with AWS Bedrock (and Agents/AgentCore), plus Lambda, API Gateway, IAM, and containerized deployments (Docker; ECS/EKS a plus).Experience with SageMaker or other ML platform services is an advantage.Programming & Open SourceExpert Python; experience building APIs and services (FastAPI or similar).Familiarity with open-source ML/NLP libraries (Hugging Face, scikit-learn, etc.) and vector databases/search.Ability to write clean, tested, maintainable production code.Data & PlatformsSolid grounding in data pipelines, warehousing, and SQL; experience with Redshift, Snowflake, or Databricks is a plus.Experience with data governance and metadata tooling (e.g., OpenMetadata) is a plus.Domain ExperienceFinancial services, trading, FX, crypto, or other regulated industry experience preferred.Understanding of data privacy, compliance, and risk considerations for AI systems.Leadership & Behavioral CompetenciesOwnership mindset and the ability to deliver independently in a lean, fast-moving team.Proven ability to lead and mentor engineers and set technical standards.Strong stakeholder management: able to translate business problems into agent designs and explain AI concepts to non-technical leaders.Pragmatic balance of engineering rigor and rapid AI-driven innovation.Why Join Us?Build and lead MBG’s agentic AI capability from the ground up, with a Group-wide mandate across Sales, Marketing, Finance, Ops, and more.Own the full agent lifecycle in production, not just prototypes.Direct access to a governed, AI-ready enterprise data foundation (EDP/EDW) and executive sponsorship.Shape AI standards, architecture, and governance at Group level, reporting to the Head of Data & AI.Work on high-impact, high-volume data in a global financial organization.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.Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.

[TW] Every 40 seconds, someone in the world dies by suicide.But long before that moment, there are often hundreds of smaller moments.A night when you can’t sleep.A breakup.Anxiety before work.The feeling that you’re losing control.Or simply a moment when you need someone to talk to and nobody is there.A therapist might be available in 6 month.A friend might be asleep.And sometimes, you don’t want to talk to either.We believe there should always be someone there. Someone you can talk to at 2:37 in the morning. That’s what we’re building.A voice-first AI companion for mental health and personal development, available to anyone, anywhere.And we’re looking for a Founding AI Voice Engineer to build it with us from zero.What you ownYou own the technology behind the product end-to-end:Build and ship iOS & Android appsBuild real-time voice-to-voice AI agents for affective full duplex dialogueSelect and integrate the right LLMs and voice modelsBuild RAG, memory and context systemsDevelop AI personas, behavior and conversational logicImplement guidelines, guardrails and safety systemsTranslate psychological frameworks into AI behavior together with expertsBuild evaluation, monitoring and testing systemsOwn backend, infrastructure and deploymentOptimize latency, quality, reliability and inference costTake the product from prototype → production → scaleExperience with clinical AI, mental health or digital health is not required, but a strong advantage.Who we’re looking forYou’ve done this before.We’re not looking for someone who wants to get into Voice AI.We’re looking for someone who has already:Built real-time speech-to-speech / voice-to-voice AI agentsDeployed them into real-world production environmentsWorked hands-on with STT, LLM and TTS pipelines and/or native speech-to-speech modelsSolved latency, interruptions, turn-taking and streamingBuilt agents capable of handling long, dynamic conversationsWorked with LLM orchestration, RAG, memory and context managementOwned systems beyond the prototype — including deployment, monitoring, reliability and scaleYou understand the difference between a voice demo that works for five minutes and a production voice agent people can actually use every day.How we workThis is early stage.No engineering team behind you. No product manager writing tickets. No six-week planning cycles.Plan in the morning. ship until the evening.We want someone who:Works extremely hardMoves extremely fastOperates independentlyTakes full ownershipFigures things out without waiting for instructionsCan go from idea to productionCares deeply about what we’re buildingYou will have enormous freedom and enormous responsibility.The missionWe are not trying to replace therapists. We want to make mental support and personal development available to anyone with a smartphone, regardless of geography, income or time of day.If we get this right, we can build something millions of people turn to when they need mental support and advice.If that’s something you want to spend the next few years building, we want to hear from you.

Job Title: VP Data Science Location: Dubai Senior Manager / VP – Data Science I’m currently supporting a leading UAE bank with the appointment of a Senior Manager – Data Science to join its growing Data function.This is a hands-on leadership role focused on delivering high-impact Data Science and Machine Learning solutions across areas including Retail Banking, Corporate Banking, Risk, Credit and Operations. The successful candidate will take complex business problems and translate them into scalable, production-ready ML solutions that deliver measurable business outcomes. We’re looking for someone with strong experience across:7+ years' Data Science / Machine Learning experienceStrong banking / financial services domain knowledgeAdvanced Python & ML developmentStatistical modelling & experimentationMLOps and productionising ML modelsGenerative AI / LLMsCloud-based ML pipelines – Azure / AWSCI/CD and modern ML engineering practicesExperience leading teams / cross-functional squads You should be comfortable owning the full ML lifecycle — from feature engineering, model selection and validation through to deployment, performance monitoring and data-drift management.

Role purposeDevelop, validate and productionise machine-learning models that improve the brokerage’s understanding of trading behaviour, execution quality and market exposure. Apply rigorous statistical methods to noisy, time-dependent financial data and convert quantitative research into reliable model services. Work with the Quantitative Lead, Dealing and Risk to ensure outputs are interpretable and appropriate for their approved use.Key responsibilitiesResearch and model developmentTranslate approved research hypotheses into features, labels and models for behavioural classification, anomaly detection, exposure forecasting and execution-quality analysis.Develop models using trading activity, price movements, order timing, holding periods, execution data and account history, with clear definitions of what each prediction represents.Investigate concentration, correlated activity, changes in trading patterns and adverse-selection indicators using supervised, unsupervised or time-series techniques as appropriate.Benchmark machine learning against transparent statistical and rules-based baselines; establish whether added complexity produces meaningful incremental value.Validation and interpretationBuild chronological and walk-forward validation that reflects live information availability; prevent leakage from overlapping labels, related accounts and future market observations.Evaluate robustness across instruments, client cohorts and market regimes, accounting for class imbalance, multiple testing and uncertainty in small samples.Include realistic spreads, slippage, latency, liquidity constraints and transaction costs when evaluating execution or hedging-related proposals.Produce explainability, calibration, sensitivity and stability analyses; document assumptions, training populations, limitations and conditions under which the model should not be used.Production models and monitoringPackage models for batch or online inference with versioned code, features, datasets and dependencies, working with MLOps on deployment and rollback.Implement model monitoring for data drift, prediction changes, performance deterioration and operational failures; distinguish changing markets from broken data.Run shadow or controlled challenger assessments before operational use, with approval and independent challenge for material trading or risk applications.Investigate model failures and refresh models through reviewed change procedures; support the Quantitative Lead in explaining results to Dealing and Risk.Essential experience and qualifications4+ years in quantitative research, applied machine learning or financial data science, with experience implementing production models.Strong Python, SQL, probability, statistics, optimisation and time-series analysis skills.Hands-on experience with tools such as scikit-learn, XGBoost, LightGBM or PyTorch and a clear ability to select methods appropriate to the problem.Working knowledge of leveraged trading, FX/CFDs or comparable electronic markets, including exposure, leverage, margin and execution costs.Demonstrated ability to prevent data leakage, conduct out-of-sample validation and evaluate model stability under changing market conditions.Strong software engineering, experiment tracking and technical documentation skills; ability to communicate uncertainty rather than overstate predictive power.Degree in Mathematics, Statistics, Computer Science, Physics, Engineering or a related quantitative discipline; postgraduate study is advantageous.Preferred experienceDirect experience with retail FX/CFD flow, broker risk books, hedging analytics or execution-quality modelling.Experience with real-time inference, high-frequency data, graph methods or interpretable client segmentation.Experience deploying models through monitored shadow testing and model review processes.

Role: Senior Data ScientistLocation: DubaiJob DescriptionSTYLI is an e-commerce marketplace founded in 2019 by Landmark Group, emerging as one of the largest fashion and beauty platforms in the GCC and India. With a strong focus on trendy, affordable fashion and beauty products, STYLI brings over 40,000 styles to men, women, kids, and beauty enthusiasts, offering them the latest global trends delivered directly to their doorsteps.Our vision is to be the most aspirational value fast fashion and lifestyle destination, delivering seamless service excellence. We aim to create personalized experiences, engaging customers across all touchpoints, and continually expanding our curated selection to meet their evolving needs. STYLI has quickly become a leading player in the e-commerce fashion space across the GCC - Saudi Arabia, UAE, Bahrain, and Kuwait and in India.Role overviewWe are looking for a highly motivated, Senior Data Scientist who enjoys solving complex and ambiguous problems using data, statistics and machine learning. You will independently own high-impact Data Science initiatives from problem definition through modelling, experimentation, productionization and impact measurement. You will work closely with Product, Engineering and business stakeholders, while also contributing technical guidance and supporting the development of the wider Data Science team.Key responsibilities● Independently solve complex business and product problems using data, statistics and machine learning.● Own Data Science projects from problem framing and data exploration through modelling, experimentation, deployment and impact measurement.● Extract, clean and analyze large datasets, and design reliable features, training datasets and evaluation frameworks.● Build, evaluate, tune and improve machine-learning, statistical or optimization models using appropriate baselines and metrics.● Conduct detailed error analysis and identify issues related to bias, leakage, data quality and model robustness.● Design and analyze experiments and other measurement approaches to estimate incremental business impact.● Work closely with Product, Engineering and business teams to integrate solutions into production workflows.● Monitor model quality, data health, operational performance and business outcomes after launch.● Make practical trade-offs across accuracy, interpretability, latency, scalability, maintainability and cost.● Write maintainable, reusable, version-controlled and well-documented code.● Communicate findings, recommendations, assumptions and risks clearly to technical and non-technical stakeholders.● Contribute to technical discussions, code and model reviews, and support other Data Scientists when needed. Data Science & AIMust-have skills and experience● Advanced proficiency in Python and SQL, with strong experience building maintainable, reusable and production-oriented Data Science code.● Strong practical experience building, evaluating and deploying machine-learning models, with depth in model selection, experimentation, error analysis and business-impact measurement.● Strong understanding of probability, statistical inference, experimental design and common sources of bias, confounding and data leakage.● Demonstrated experience independently owning multiple Data Science initiatives from problem framing through production and post-launch monitoring.● Experience designing reliable training and evaluation datasets and identifying upstream data-quality or instrumentation gaps.● Working knowledge of production ML concepts, including batch or real-time inference, APIs, CI/CD, model monitoring and retraining.● Ability to make sound technical trade-offs across model quality, latency, scalability, maintainability and infrastructure cost.● Strong stakeholder-management and communication skills, with the ability to influence product and business direction through data and deliver measurable customer or business impact.● A proactive, outcome-oriented mindset with the ability to operate effectively under ambiguity, take ownership without close supervision, and provide constructive technical guidance to others.Good-to-have skills● Strong experience in one or more areas such as recommendation systems, search and ranking, forecasting, pricing, optimization, customer modelling, causal inference, computer vision or generative AI.● Familiarity with distributed processing, orchestration, backend APIs, cloud deployment, search or vector databases, caching technologies and model-serving systems.● Experience in e-commerce, retail, fashion or another large-scale digital product environment.Education and experience● Bachelor's, Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, Operations Research or a related quantitative field.● Typically 5+ years of relevant Data Science or applied machine-learning experience; equivalent depth, scope and demonstrated impact will also be considered.What success looks likeA successful Senior Data Scientist will independently solve complex problems, apply strong technical judgement, deliver reliable production solutions, influence cross-functional decisions and create measurable customer or business impact. Data Science & AI

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 DescriptionAbout the Applied AI TribeThe Applied AI Tribe is talabat's internal AI engine, a team obsessed with turning cutting-edge AI into genuine, measurable business value. We don't build AI for its own sake. Our north star is Net AI Value Delivered.We have shipped 40+ AI products across four strategic streams: Product & Tech Platform - AI capabilities embedded into talabat's core product and engineering platform. Business Automations - streamlined workflows that save real time and money across operations. Self-Serve AI Tools - empowering talabatis to build and use AI without needing to raise a ticket. Training & Onboarding - upskilling the tribe so every team can participate in the AI era.Our engineering approach is built around shipping agentic AI systems at scale, with a harness-first philosophy, evaluation embedded into every product iteration, and production feedback loops that drive the roadmap.The RoleAs Manager, Data Scientist - AI within the Applied AI Tribe, you will lead a team of data scientists building and shipping the ML and generative AI systems that power decisions across talabat's product and business. You are equally a people leader and a technical practitioner, close enough to the work to make great technical decisions and grow your team, while owning the roadmap and delivery.Your team's work spans the full AI lifecycle: from framing ambiguous business problems through data modelling, feature engineering, model training, deployment, and production monitoring. A significant focus will be leveraging LLMs, agentic systems, and generative AI to automate decisions, enrich data, and build intelligent experiences at scale, all measured against Net AI Value Delivered.What's On Your Plate?People Leadership: Lead, grow, and retain a team of data scientists, setting a high bar for technical quality, fostering a culture of ownership, and supporting each person's career development. Partner with recruiting to attract top data science and ML talent as the tribe scales. Mentor team members in ML best practices, agentic system design, production engineering, and stakeholder communication. Run effective team rituals, planning, design reviews, retrospectives, that keep the team aligned and moving with pace.Technical Strategy & Delivery: Translate ambiguous business problems into well-scoped ML and AI solutions with clear, measurable success criteria tied to the tribe's north star. Own the team's technical roadmap: prioritise high-impact work across data enrichment, business automation, self-serve tooling, and agentic product features. Champion harness-first thinking, ensure evaluation pipelines, LLM observability, tooling, and infrastructure are in place before agent logic is built on top. Embed evaluation into every product iteration: golden datasets, stakeholder-aligned metrics, and weekly eval jobs that guide what gets built, fixed, or retired. Oversee the full ML lifecycle: data pipelines, feature engineering, model training, production deployment, serving, and monitoring. Drive adoption of LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making at scale. Design and analyse experiments (A/B and multivariate) to rigorously measure model and product impact. Elevate ML and engineering standards across the team, improving MLOps, code quality, tooling, and internal learning programmes.Cross-functional Partnership: Partner with product managers and business teams to identify high-value AI opportunities and shape them into the team's roadmap. Communicate clearly with senior stakeholders, from problem framing through to results and recommendations. Collaborate with engineering teams to understand data systems, build reliable data models, and ensure smooth production integration.QualificationsWhat Did We Order?Technical Experience Deep expertise in machine learning, generative AI, deep learning, NLP, recommendation systems, and data mining. Hands-on knowledge of ML and GenAI frameworks: Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Transformers, and LLM fine-tuning. Proficiency with the OpenAI SDK and familiarity with major LLM provider APIs for building and orchestrating production AI systems. Hands-on experience with LangGraph for building stateful, multi-step agentic workflows and complex agent orchestration patterns. Experience with Hugging Face (Transformers, Hub, Inference API) for model sourcing, fine-tuning, and deployment. Solid understanding of embeddings, dense and sparse retrieval, vector databases, and semantic search, for building RAG pipelines and similarity-based applications. Strong software engineering fundamentals: clean production code, data structures and algorithms, ML system design. Proven experience shipping and monitoring ML models in production, with a solid grasp of MLOps practices. Strong data and ML engineering skills: building and orchestrating data pipelines (e.g., Airflow) and robust feature engineering. Excellent SQL and Python; solid statistical foundations including experiment design, causal inference, and predictive methods. Familiarity with agentic system design (harness-first thinking, LLM observability, evaluation pipelines, and production feedback loops) is a strong plus. Experience with BigQuery and Google Cloud Platform is a plus.Qualifications Bachelor's degree in Engineering, Computer Science, or a related field. A postgraduate degree is a plus. 6+ years of experience in data science, ML engineering, and/or generative AI, including shipping models to production. 2+ years managing or leading a data science or ML team, with a track record of developing talent and delivering through others. Experience building ML systems in an online consumer product environment is a strong plus.Additional InformationMindset & Ways of Working Curiosity over certainty: you're excited to try the new model or framework this week. Ownership: you treat cost, latency, and business impact as your problem, and your team's. Bias to build: a prototype in a real workflow beats a perfect design doc every time. Comfortable with ambiguity: most of what we build has no playbook yet, and you help write it. Keep it simple: pick the approach that delivers the most value with the least complexity, and #makeithappen.At talabat, your success is defined by both results and behaviors. We hire for excellence in craft and for the Leadership Principles that shape how we think, decide, and collaborate. What you achieve matters, and how you achieve it defines us. Together, they move the business forward and deliver great experiences. Learn more about our Leadership Principles here.

Role: Machine Learning EngineerLocation: Dubai Department: Technology & OperationsReports To: CTOPosition: Full-TimeAbout us:GlobalDrum is empowering the media sector to own, understand, and monetise their most valuable social audiences, using live audience behavioral data for brands to operate diversified business models on demand for themselves. We are evolving our unique next-generation B2B2C Platform as a Service (PaaS) that operates on a globally distributed cloud infrastructure incorporating a scalable, event-driven architecture using the latest AI and data techniques to evolve an entire sector.Located in London, Dubai, New York and Dubai, the Company is at the centre of reshaping how global brands will evolve in a sector valued at $276Bn in 2025 representing 30% of all digital ad spending. If this seems too ambitious for you, then don't apply. Job Description:We are looking for a visionary Machine Learning Engineer to become our first-ever ML hire, embedding data science and applied ML into the heart of our AI-native, multi-tenant platform. You will work directly with the Director of Engineering and product owners to turn audience, content, and revenue data into models that power recommendations, audience understanding, and monetisation decisions across the platform.This is a rare opportunity to define the ML function from the ground up: choosing the stack, setting the standards, and building the first production models that the rest of the engineering org will be built around.Key Responsibilities:Own Recommendations End-to-End: Design, build, and iterate on recommender systems that surface content and audience opportunities to our media partners.Build the ML Foundation: Establish the first ML pipelines, feature stores, experimentation frameworks, and model-serving infrastructure for the platform, since none currently exist.Data-to-Product Pipeline: Partner with the engineering team to design real-time, event-driven data pipelines that feed model training and low-latency inference.Experimentation & Evaluation: Define offline and online evaluation methodology (A/B testing, holdout sets, ranking metrics) to validate model impact on engagement and revenue.Set ML Standards: Establish best practices for model development, versioning, reproducibility, monitoring, and responsible use of data Stay Hands-On: Write production-grade ML code, heavily leveraging modern AI coding assistants and agentic development workflows to move fast as a team of one (initially).Cross-Functional Partnership: Work closely with the Engineering and platform/revenue product owners to translate business and product questions into ML-solvable problems.Scale the Function: As the first ML hire, help define the roadmap and hiring plan for the ML team as it grows.Required Skills and Qualifications:Proven, hands-on experience building and deploying recommender systems in production Working knowledge of graph-based learning, including Graph Neural Networks.Solid understanding of network science fundamentals.Experience designing and training models on large-scale, real-world data, including handling sparsity, and skewed engagement distributions.Comfortable owning the full ML lifecycle: feature engineering, training, evaluation, deployment, and monitoringFluency with modern ML tooling (e.g., PyTorch/TensorFlow and standard MLOps practices).Experience using AI coding assistants and agentic workflows to accelerate development.Track record of working effectively in an early-stage startup environment.Bonus Points If You Have...Exposure to the media and/or news technology ecosystem.Experience in AdTech: advertising networks, ad serving, audience segmentation.Preferred Experience/Qualifications:Strong domain knowledge in SaaS/PaaS, MarTech, or AdTech is highly valued.Experience building models that directly optimize platform revenue outcomes.Experience building recommendation systems in production using LLMs and VLMsComfortable being the sole ML voice in the room initially, while communicating clearly with engineering and product stakeholders who may not have deep ML backgroundWhy Join Us?The chance to build a ground-breaking AI platform from day oneCompetitive equity options package and salaryFlexible working environment

Principal Data Scientist – Generative AI & Agentic SystemsLocation: Dubai, UAEWe are looking for an exceptional Principal Data Scientist to lead the design and delivery of advanced AI solutions, with a particular focus on Generative AI, agentic systems and production-grade RAG architectures.This is a highly hands-on technical role. The successful candidate will remain close to the code while providing technical leadership, owning complex solution domains and translating real business problems into scalable AI products.What you'll be doing- Design and build complex agentic RAG systems, multi-step AI workflows and LLM-powered applications.- Lead AI solutions end-to-end, from experimentation and architecture through production deployment, monitoring and continuous improvement.- Write and review production-quality Python and modern AI/ML code.- Own solution architecture, technical standards and engineering best practices across AI initiatives.- Provide technical leadership and mentorship while remaining an active hands-on contributor.- Evaluate and apply emerging models, frameworks, vector databases, orchestration tools and AI engineering approaches.- Work closely with business stakeholders to ensure AI initiatives deliver measurable commercial and operational value.- Build robust data and model pipelines, testing, evaluation, observability and MLOps practices.What we're looking for- 8+ years of relevant experience across Data Science, Machine Learning, AI Engineering or closely related areas.- Strong recent experience building complex agentic RAG systems, beyond standard question-answering chatbots.- Deep practical knowledge of LLMs, retrieval, embeddings, vector databases, agent orchestration and production AI architectures.- Strong hands-on Python skills and current software engineering practices, including APIs, testing, version control, CI/CD and maintainable production code.- Demonstrated technical leadership, team leadership or ownership of a significant technical domain.- A track record of translating AI capabilities into measurable business outcomes.- Experience operating in demanding, technically sophisticated environments.- Broader experience across different organisations, products or business domains is highly valued.Nice to have- Experience productising AI and ML solutions within the Microsoft Azure ecosystem.- Cloud-native architecture and deployment experience.- Strong MLOps and data engineering exposure.- Experience taking Generative AI products from prototype through to reliable production use.This opportunity is particularly suited to a senior technical leader who still enjoys building, coding and solving difficult AI problems directly rather than operating primarily as a people or vendor manager.

DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. We combine deep quantitative expertise, cutting-edge cloud architecture, and modern MLOps to engineer secure, scalable, and resilient platforms designed to power enterprise AI at scale.With deep roots across the financial services and banking sectors in the UAE, we help major institutions bridge the gap between experimental models and production-grade AI platforms. We don't build temporary fixes or isolated prototypes—we engineer bulletproof, banking-grade AI solutions for high-stakes enterprise transformations.The OpportunityWe are seeking an exceptional Principal AI / ML Engineer to serve as a technical authority, team mentor, and trusted client principal across our high-impact enterprise engagements in the UAE.This is a high-visibility leadership role at the intersection of quantitative science, deep learning architectures, modern MLOps, and strategic consulting. You will lead cross-functional squads of AI Engineers, Data Scientists, and Data Engineers—translating complex executive visions into elegant, production-ready machine learning and Generative AI systems while navigating client organizations with high emotional intelligence (EQ), empathy, and poise.What You'll Do...Architect, build, and deploy enterprise-grade machine learning models, deep learning pipelines, Retrieval-Augmented Generation (RAG) systems, and LLM agent frameworks on modern cloud infrastructure (AWS, Azure)Act as the primary technical advisor to client C-suite, Chief AI Officers, and Engineering Leads. Translate complex business challenges into clear technical execution blueprints, evaluation harnesses, and delivery roadmapsDirect and nurture a team of AI engineers and quantitative specialists. Build a culture of psychological safety, continuous learning, and technical excellence through hands-on coaching and active listeningUse high EQ to de-escalate project friction, align disparate business and IT agendas, and defend technical choices, explainability models, and AI ethics before architecture review boards (ARBs) and risk committeesDesign zero-trust AI security frameworks, prompt injection defences, PII masking protocols, and automated CI/CD pipelines compliant with regional Central Bank regulatory frameworks and data sovereignty lawsAs an AI consultancy, our greatest asset is the expertise of our people.While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.RequirementsWhat We're Looking For...A Master's or Bachelor's degree in Mathematics, Theoretical Physics, Physics, Computer Science, or a related quantitative field8+ years in software engineering, machine learning, and AI platform development, with substantial experience leading teams inside top-tier technology or management consultanciesDemonstrated ability to build authentic client trust, read organizational dynamics, resolve technical friction constructively, and lead teams with empathy and clarityDeep technical command of modern AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex), vector databases, container orchestration (Docker, Kubernetes), and cloud MLOps (AWS SageMaker, Azure OpenAI)Proven track record of taking complex AI/ML systems out of experimental notebooks and into secure, high-concurrency production cloud environmentsWhile we welcome expertise across complex enterprise industries, a background in financial services, banking, or capital markets is highly advantageousWhat Gives You an Edge...Practical experience with parameter-efficient fine-tuning (LoRA, QLoRA), quantization, and serving open-weight LLMs (vLLM, Ollama, TGI)Hands-on experience designing concurrent multi-cloud AI architectures across AWS and Azure in regulated environmentsExperience navigating enterprise procurement, client dynamics, and local regulatory frameworks across the UAE or broader GCC regionBenefitsThe benefits you'll enjoy as part of this role include:Competitive salaryComprehensive 'Gold Level' personal health insurance Individual Visa SponsorshipProfessional development and certification supportSubscription reimbursement relating to your roleOpportunity to work on cutting-edge AI projectsMonthly Employee Incentive programCareer advancement opportunities in a rapidly growing AI companyThis position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

Job DescriptionWe 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 will design, develop, and apply advanced data science, statistical, and machine learning methods to solve complex business problems. Embedded within customer engagements and fast-paced delivery teams, you will translate business challenges into scalable analytical and AI solutions that deliver measurable outcomes. Working closely with customers, engineers, and product teams, you will build production-ready machine learning and Generative AI solutions while continuously improving model quality, performance, and business impact.In This Role, You WillTransform business challenges into data-driven solutions by identifying analytical opportunities, exploring data, engineering features, and developing predictive models.Design, develop, train, evaluate, and optimize machine learning models and statistical solutions for enterprise business scenarios.Apply techniques across exploratory data analysis, forecasting, classification, clustering, recommendation systems, anomaly detection, experimentation, causal analysis, and predictive analytics.Develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and Agentic AI frameworks.Integrate analytical and AI solutions into enterprise applications and business processes, ensuring scalability, robustness, and production readiness.Define evaluation metrics, validate model performance, monitor deployed models, and continuously improve solution accuracy and reliability.Work closely with customer teams to understand business processes, data landscapes, and operational challenges to co-create impactful AI solutions.Collaborate with AI Engineers, Data Engineers, Product Managers, and UX teams to deliver end-to-end AI products.Communicate analytical findings, technical trade-offs, and solution recommendations clearly to engineering teams and customer stakeholders.Stay current with the latest advancements in Data Science, Machine Learning, Generative AI, and Agentic AI, applying emerging techniques where appropriate. What You BringStrong hands-on expertise in Data Science, Machine Learning, and Applied AI with excellent proficiency in Python and SQL.Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies.Strong understanding of statistics, probability, hypothesis testing, experimental design, model evaluation, and feature engineering.Experience developing predictive models, recommendation systems, forecasting models, anomaly detection, and classification algorithms.Hands-on experience with Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.Experience deploying machine learning and AI solutions using cloud-native platforms and modern MLOps practices.Familiarity with SAP data landscapes including SAP S/4HANA, SAP HANA Cloud, SAP BW/4HANA, SAP Business Technology Platform (BTP), AI Core, AI Launchpad, and SAP AI services is an advantage.Ability to translate ambiguous business requirements into practical analytical solutions while balancing model accuracy, interpretability, scalability, and business value.Strong communication, collaboration, and problem-solving skills with the ability to work effectively in customer-facing environments.You proactively leverage AI in your everyday workflows, ensuring high-quality outcomes through thoughtful context design, experimentation, and system integration. Where you belong You will be part of a growing AI and industry expert team dedicated to serving customers across the Americas, Europe, and Asia. We bring together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate and lead in their markets. You’ll collaborate with cross-functional teams to solve challenging business problems, build enterprise-grade AI solutions, and deliver measurable customer value. This is a place for curious builders who enjoy learning, experimenting, and applying AI to real-world business challenges.#SAPIndustryAICareers #SAPAICareersBring 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: 457241 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations:Job DetailsRole Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://www.sap.com Job Function: Data Science & AI Company Industry/Sector: Software DevelopmentWhat 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.

Job SummaryAs a Forward Deployed AI Engineer, Technical Lead you set the technical direction for a squad embedded in the business: you sit with stakeholders to understand the problem and the why, then design, build, deploy and run the agentic AI systems that solve it, end to end. This is a hands-on, build-first role with single-threaded ownership of a real aviation outcome, working alongside a Business Product Owner and an AI Value Architect, on a shared platform (paved road, MCP fabric, standards) that lets your squad self-serve against client systems.Accountabilities & ResponsibilitiesUnderstand before you build. Start every problem with the business need and the why, working directly with stakeholders, then take the solution from discovery to production.Design, build, deploy and continuously improve enterprise-grade agentic AI applications for real aviation scenarios, using agentic coding as your default way of working.Build agents that reason across steps, call tools and APIs, manage context, handle exceptions and support human-in-the-loop, reliably and at enterprise scale.Design and implement RAG pipelines over enterprise knowledge: ingestion, chunking, embeddings, vector search, retrieval tuning, grounding and source traceability.Build MCP-based integrations and connect agents to backend systems via REST/OpenAPI, webhooks and event-driven patterns with secure authentication, and expose your own work as clean, reusable, self-serviceable interfaces.Apply structured LLM patterns end to end: tool calling, schema-validated outputs, retries, fallbacks and guardrails.Own quality from day one: testing, evaluation, observability, logging, versioning and feedback loops for reliability, accuracy, latency, security and cost.Apply security, privacy, access control, auditability, responsible-AI and governance across every deployment.Take single-threaded ownership of a domain outcome (one owner, one result), and help establish reusable patterns that grow Etihad’s internal AI capability rather than renting it.Coordinate with your Business Product Owner, AI Value Architect and other squads; speak up when AI is not the right tool.Set the technical direction and standards for the squad’s agentic AI work, and make the key architecture and build-vs-buy calls.Design multi-agent and agent-to-agent systems and the evaluation frameworks that keep them reliable, and lead delivery with external AI platforms and vendors while building Etihad’s internal capability.Grow the engineers around you: mentor, review, and raise the bar on quality, security and cost across the squad. Education & ExperienceWe look for a technical lead who sets the engineering direction for agentic AI while still building, and combines that with a business-first mindset:Curiosity above all: you dig into problems, question assumptions and want to understand how the airline actually works.A business-first, human-centric mindset: aviation is made for humans, by humans, and AI supports people, it does not replace them. Fluent English, comfortable in a culturally diverse, international team.8+ years building production-grade software, including 4+ years with GenAI, LLMs and applied ML and at least 1 year of hands-on agentic AI as an early adopter, with a track record of setting technical direction and shipping agentic systems at scale.Hands-on experience or strong working knowledge of MCP (Model Context Protocol) for connecting agents to tools, systems, APIs and data.Strong Python, with strong knowledge of at least one of TypeScript / JavaScript, Java, or C#, and modern engineering practice: async programming, FastAPI, Pydantic, Git and CI/CD, testing, error handling and logging.Practical experience with at least one agent framework or enterprise AI platform (e.g. LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Foundry, Amazon BedrockAgentCore, Google Vertex/Gemini) and with a vector database or search platform (e.g. Azure AI Search, pgvector, Pinecone, Weaviate, OpenSearch).Experience integrating enterprise systems (APIs, managed identities, webhooks, queues, middleware) and deploying on cloud with containers, monitoring and observability; sound judgement on the trade-offs of latency, quality, cost and reliability, and on security, privacy, responsible AI and governance.Strong assets: aviation or airline domain knowledge; a background in classical machine learning and data science; and classical full-stack development (interfaces, frontends, APIs, backend engineering).Master’s degree in Computer Science, Software Engineering, Data Science, AI/ML or a related technical field, or equivalent practical experience; relevant cloud-AI, GenAI, agentic-AI or MLOps certifications are an advantage.Preferred For This LevelExperience building AI agents for complex enterprise or operations-heavy workflows (logistics, supply chain, aviation, cargo, customer operations or contact centre).Experience with voice AI, email automation, CRM integrations, workflow automation or multilingual agents.Experience designing golden test sets, simulation-based testing, regression testing and agent evaluation frameworks.Experience designing multi-agent systems and agent-to-agent communication patterns, agent registries or tool-orchestration standards.Experience leading delivery with external AI platforms, startups or vendors while building internal engineering capability.Growth path: the natural next step is AI Value Architect, owning a cluster’s value journey while still building alongside the team.

Job DescriptionOrganization Unit PurposeEmirates NBD is one of the largest banks in the Middle East, with over USD 6Bn in revenues and 14000 employees globally. As part of its strategic mandate, the bank has recently setup its Advanced Analytics Centre of Excellence for driving ENBD’s ambitious advanced analytics agenda across ENBD.Core objectives of the center include: Deliver 500-800 Mn AED business impact through a series of use cases/ AA projects executed in collaboration with the BU’s Instill a data driven culture across ENBD by building organization wide capabilities in advanced analyticsThe CoE will act as an enabler to the BUs to deploy advanced analytics models to drive smarter decisions across different domains. It will act as a guiding light to BUs to ideate on what’s possible with advanced analytics, help them prioritize these ideas, and pilot and productionalize them through cross-functional AA squads.It will house highly skilled data scientists, data engineers and other digital talent that will be an integral part of cross-functional squads that execute AA projects.The AA agenda is a high visibility and high priority initiative for ENBD. AA CoE will be governed at ExCo level, including impact tracking, a ringfenced budget & performance managementJob PurposeThe data scientist scopes, designs, and implements machine-learning models to support use case execution with a view of achieving overall objectives and targetsThe role is highly collaborative and works with product owners, business translator, data warehousing and data engineering teams in creating big data applications through the utilization of structured and unstructured data, designing optimal data architecture, and experimenting on new machine learning techniquesThe senior data scientist is expected to take charge of end to end delivery of machine learning models including regularly testing and maintain analytical models to improve efficiency and keep up with changing business needsThe role supports Translators in communicating the design, functioning and output of the analytical models/solutions developedThe senior data scientist additionally plays a mentorship role to others in the team, guiding junior colleagues in execution of their duties, and mentoring them in their professional growthJob ContentDeliver a strong roadmap of AA projects in collaboration with Business UnitsDesigns and implement machine-learning models to support the business’s numerous initiatives and programs with a view of achieving overall objectives and targetsArtefact documentationSuccessful documentation of reusable codeDevelopment and learningAchieve personal technical development and learning goalsCollaboration and knowledge shareConduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etcParticipates in and helps plan cultural initiatives for CoEQualificationsEducationUniversity degreeAdvanced degree (MS/Ph.D) in Computer Applications, Economics, Statistics or Mathematics or related technical discipline with high analytical rigor is desirableExperiences6-8 years of experience in a data science role is essentialKnowledge & SkillsValidated experience of defining analytics road map and leading analytics engagementsShould have experience in machine learning, statistics, optimization or related fieldsExperience with programming is a must; specifically experience in R or PythonExperience of working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) is essentialStrong analytical and problem-solving skillsWorked in agile environments with multiple stakeholders from the businessBehavioral CompetenciesPractical and action orientedCompelling communicatorExcellent stakeholder managementFoster and promote entrepreneurial spirit and curiosity amongst team membersTeam playerQuick learnerThere’s never been a better time to join Emirates NBD. We’re one of the region’s most recognizable brands. We’re banking innovation leaders. We’re growing across both the UAE and our global offices. We offer a huge range of professional development opportunities to accelerate your career. It also goes without saying that we provide extremely competitive rewards, benefits and perks too, like our flexible work policy so you can work from home whenever it suits.At ENBD, we encourage interested candidates to review the key responsibilities and qualifications for each role and apply for positions that match their skills and capabilities.

DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. We combine deep quantitative expertise, cutting-edge cloud architecture, and modern MLOps to engineer secure, scalable, and resilient platforms designed to power enterprise AI at scale.With deep roots across the financial services and banking sectors in the UAE, we help major institutions bridge the gap between experimental models and production-grade AI platforms. We don't build temporary fixes or isolated prototypes—we engineer bulletproof, banking-grade AI solutions for high-stakes enterprise transformations.The OpportunityWe are seeking an exceptional Principal AI / ML Engineer to serve as a technical authority, team mentor, and trusted client principal across our high-impact enterprise engagements in the UAE.This is a high-visibility leadership role at the intersection of quantitative science, deep learning architectures, modern MLOps, and strategic consulting. You will lead cross-functional squads of AI Engineers, Data Scientists, and Data Engineers—translating complex executive visions into elegant, production-ready machine learning and Generative AI systems while navigating client organizations with high emotional intelligence (EQ), empathy, and poise.What You'll Do...Architect, build, and deploy enterprise-grade machine learning models, deep learning pipelines, Retrieval-Augmented Generation (RAG) systems, and LLM agent frameworks on modern cloud infrastructure (AWS, Azure)Act as the primary technical advisor to client C-suite, Chief AI Officers, and Engineering Leads. Translate complex business challenges into clear technical execution blueprints, evaluation harnesses, and delivery roadmapsDirect and nurture a team of AI engineers and quantitative specialists. Build a culture of psychological safety, continuous learning, and technical excellence through hands-on coaching and active listeningUse high EQ to de-escalate project friction, align disparate business and IT agendas, and defend technical choices, explainability models, and AI ethics before architecture review boards (ARBs) and risk committeesDesign zero-trust AI security frameworks, prompt injection defences, PII masking protocols, and automated CI/CD pipelines compliant with regional Central Bank regulatory frameworks and data sovereignty lawsAs an AI consultancy, our greatest asset is the expertise of our people.While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.RequirementsWhat We're Looking For...A Master's or Bachelor's degree in Mathematics, Theoretical Physics, Physics, Computer Science, or a related quantitative field8+ years in software engineering, machine learning, and AI platform development, with substantial experience leading teams inside top-tier technology or management consultanciesDemonstrated ability to build authentic client trust, read organizational dynamics, resolve technical friction constructively, and lead teams with empathy and clarityDeep technical command of modern AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex), vector databases, container orchestration (Docker, Kubernetes), and cloud MLOps (AWS SageMaker, Azure OpenAI)Proven track record of taking complex AI/ML systems out of experimental notebooks and into secure, high-concurrency production cloud environmentsWhile we welcome expertise across complex enterprise industries, a background in financial services, banking, or capital markets is highly advantageousWhat Gives You an Edge...Practical experience with parameter-efficient fine-tuning (LoRA, QLoRA), quantization, and serving open-weight LLMs (vLLM, Ollama, TGI)Hands-on experience designing concurrent multi-cloud AI architectures across AWS and Azure in regulated environmentsExperience navigating enterprise procurement, client dynamics, and local regulatory frameworks across the UAE or broader GCC regionBenefitsThe benefits you'll enjoy as part of this role include:Competitive salaryComprehensive 'Gold Level' personal health insurance Individual Visa SponsorshipProfessional development and certification supportSubscription reimbursement relating to your roleOpportunity to work on cutting-edge AI projectsMonthly Employee Incentive programCareer advancement opportunities in a rapidly growing AI companyThis position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

About the CompanyCareem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.About The TeamThe Personalization team sits within Careem's Data Science organization and owns the AI systems that decide what every user sees, in what order, and why across Food, Quik, and Shops. Our mission is to build the hyper-personalization layer for the Careem app: real-time, cross-vertical recommendation and ranking systems that learn from a user's behavior in one vertical and apply that understanding everywhere else they engage with Careem. As one of the senior technical leads on this team, you'll help define how Careem thinks about personalization at a regional scale working alongside the region's top data science talent, and pushing the state of the art using graph-based retrieval, transformer architectures, and real-time learning.What You'll DoOwn hyper-personalization use cases across Food, Quik, and Shops designing systems that learn a user's intent and preferences in real time and transfer that signal across verticals, so a user's behavior on one product makes every other product smarter.Be a technical lead on Careem's exploration of graph-based retrieval methods for recommendations including evaluating and building knowledge graph pipelines that power candidate generation and ranking at scale.Design and evaluate transformer-based architectures (XFY) for sequential and contextual recommendation moving Careem's ranking and retrieval stack beyond classical ML toward deep, attention-based models.Push toward online/streaming learning systems that adapt to user behavior within a session, not just from batch-trained models refreshed on a daily cadence.Identify where personalization signals, models, or infrastructure can be shared across Food, Quik, and Shops rather than rebuilt per vertical reducing duplicate work and compounding the value of every experiment.Be part of a 0-to-1 AI transformation for the Careem app from a personalization standpoint shaping how generative AI and LLM-based systems augment retrieval and ranking.Build a long-term vision for how Careem rethinks customer acquisition and engagement strategies, grounded in data-driven decision-making.Drive exploratory analysis to understand user behavior across verticals, identifying new levers to move metrics and building behavioral models that inform product enhancements.Shape and influence the ML models and instrumentation that optimize the product experience, surfacing new areas of opportunity and new product directions.Provide product leadership through data-driven recommendations communicating the state of the business, root-causing metric movements, and using experimentation results to influence product and business decisions.Implement scalable machine learning algorithms that run in production on large-scale data.Run exploratory data analysis to better understand user and business phenomena, and to discover untapped areas of growth and optimization.Answer complex analytical questions from large datasets to help shape Careem's products and services.Define and track key metrics for specific personalization initiatives.Design and run randomized controlled experiments (A/B tests), analyze results, and communicate findings to cross-functional teams.Continually challenge the status quo investigating new data processing technologies, retrieval architectures, and learning paradigms, and ensuring the team operates at industry-leading standards.Build and deploy retrieval-augmented generation (RAG) systems and other applications of large language models within the personalization stack.What You'll Need7-10 years of experience in data mining, predictive modeling, time series analysis, machine learning, and Big Data methodologies, including transformation and cleaning of structured and unstructured data.Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering, or Computer Science.Solid experience with deep learning techniques including attention mechanisms, retrieval models, and transformer-based architectures (XFY or similar) applied to ranking or recommendation problems. Working with or evaluating knowledge graphs, graph neural networks, or graph-based retrieval systems is a strong plus. Careem is actively building toward graph-based retrieval for recommendations.2-4 years of industry experience in personalization, recommendation, or search is a MUST. Preferably gained in a product-driven company operating at scale.Strong problem-solving and coding skills.Solid knowledge of A/B testing methodology, classical ML, and deep learning.Solid understanding of recommendations, ranking, and retrieval systems end-to-end.Familiarity with or interest in online/streaming learning systems models that adapt within a session rather than relying solely on batch retraining, is a strong plus.Proficiency and demonstrated experience in Python, SQL, Spark, and Hive.Demonstrated experience with database technologies (e.g. Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik); geospatial data processing skills are a plus.What We'll Provide YouWe offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:Work and learn from great minds by joining a community of inspiring colleagues.Put your passion to work in a purposeful organization dedicated to creating impact in a region with a lot of untapped potential.Explore new opportunities to learn and grow every day.Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year.Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

Job DescriptionOrganization Unit PurposeEmirates NBD is one of the largest banks in the Middle East, with over USD 6Bn in revenues and 14000 employees globally. As part of its strategic mandate, the bank has recently setup its Advanced Analytics Centre of Excellence for driving ENBD’s ambitious advanced analytics agenda across ENBD.Core objectives of the center include: Deliver 500-800 Mn AED business impact through a series of use cases/ AA projects executed in collaboration with the BU’s Instill a data driven culture across ENBD by building organization wide capabilities in advanced analyticsThe CoE will act as an enabler to the BUs to deploy advanced analytics models to drive smarter decisions across different domains. It will act as a guiding light to BUs to ideate on what’s possible with advanced analytics, help them prioritize these ideas, and pilot and productionalize them through cross-functional AA squads.It will house highly skilled data scientists, data engineers and other digital talent that will be an integral part of cross-functional squads that execute AA projects.The AA agenda is a high visibility and high priority initiative for ENBD. AA CoE will be governed at ExCo level, including impact tracking, a ringfenced budget & performance managementJob Purpose The data scientist scopes, designs, and implements machine-learning models to support use case execution with a view of achieving overall objectives and targets The role is highly collaborative and works with product owners, business translator, data warehousing and data engineering teams in creating big data applications through the utilization of structured and unstructured data, designing optimal data architecture, and experimenting on new machine learning techniques The data scientist is expected to take charge of end to end delivery of machine learning models including regularly testing and maintain analytical models to improve efficiency and keep up with changing business needs The role supports Translators in communicating the design, functioning and output of the analytical models/solutions developed The data scientist additionally plays a mentorship role to others in the team, guiding junior colleagues in execution of their duties, and mentoring them in their professional growthJob ContentDeliver a strong roadmap of AA projects in collaboration with Business UnitsDesigns and implement machine-learning models to support the business’s numerous initiatives and programs with a view of achieving overall objectives and targetsArtefact documentationSuccessful documentation of reusable codeDevelopment and learningAchieve personal technical development and learning goalsCollaboration and knowledge shareConduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etcParticipates in and helps plan cultural initiatives for CoEQualificationsEducationUniversity degreeAdvanced degree (MS/Ph.D) in Computer Applications, Economics, Statistics or Mathematics or related technical discipline with high analytical rigor is desirableExperiences6-8 years of experience in a data science role is essentialKnowledge & SkillsValidated experience of defining analytics road map and leading analytics engagementsShould have experience in machine learning, statistics, optimization or related fieldsExperience with programming is a must; specifically experience in R or PythonExperience of working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) is essentialStrong analytical and problem-solving skillsWorked in agile environments with multiple stakeholders from the businessBehavioral CompetenciesPractical and action orientedCompelling communicatorExcellent stakeholder managementFoster and promote entrepreneurial spirit and curiosity amongst team membersTeam playerQuick learnerThere’s never been a better time to join Emirates NBD. We’re one of the region’s most recognizable brands. We’re banking innovation leaders. We’re growing across both the UAE and our global offices. We offer a huge range of professional development opportunities to accelerate your career. It also goes without saying that we provide extremely competitive rewards, benefits and perks too, like our flexible work policy so you can work from home whenever it suits.At ENBD, we encourage interested candidates to review the key responsibilities and qualifications for each role and apply for positions that match their skills and capabilities.

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

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

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.

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.

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.

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:

Murphy deploys AI agents for banks starting with the most straightforward business case: voice AI for debt collection. We’ve built a fully-fledged platform designed to optimize recovery rates while maintaining respectful and personalized communication.Our AI-powered agents adapt instantly, engaging with debtors across channels like voice, messengers, email and SMS to maximize results while preserving trust.We’re live with Santander, Revolut, BBVA and dozens others. We’ve proven the product in large-scale pilots with top-tier banks. And now we need to move fast to secure leadership in this $300Bn+ industry.About The RoleWe're looking for a Data Scientist to build the Murphy’s brain — the ML that decides who we contact, when, how and how often, to recover the most debt inside hard legal limits. Recovery is a data problem before it's a voice problem, and you own the data problem. This is one of the highest-leverage seats in the company: your models set the strategy every AI agent executes, on every call.Murphy builds AI voice agents that collect overdue debt for banks: more recovered, faster, cheaper, fully compliant, and respectful to the debtor. We're live with Santander, Revolut, BBVA and dozens others. We've proven the product in large-scale pilots with top-tier banks — now we're making every contact smarter, and we need a scientist to own the models that decide how we collect.What you'll doOwn the contact strategy. Who Murphy contacts, when, how often, on which channel — voice, WhatsApp, etc. — to maximise recovery inside hard legal guardrails.Model the debtor. Propensity and uplift models — who picks up, who pays, who responds to which voice, script or offer — turned into live segments the agents act on.Optimise with experiments. A/B tests and bandits over timing, cadence, voice and negotiation policy; find what lifts recovery, and ship it fast.Own business-level outcomes. Collaborate with product, engineering and commercial teams to define solutions and improve the key metrics.Who you areYou hold a degree in mathematics, statistics, machine learning, or computer science.Rigorous with probability and statistics. Experimental design, causal inference. You reach for the right tool, and you know when a result is real.AI-native, ruthless on quality. You reach for AI to automate and streamline by default — and you know exactly where it gets sloppy. You never let that through, and you control quality rigorously.You don’t need a collections or fintech background. We’d rather teach the domain to a killer than hire a lifer who can’t ship — you’ll pick up the domain, the data and the regulation cold, fast.Requirements2+ years shipping ML that ran in production and moved business metrics. Models that pick the best next action and measure whether it actually changed the outcome; ranking, pricing or contact-strategy models. Models that ship as code, not notebooks.Expert Python. Comfortable in a real production codebase — you take a model from idea to production and monitor it. We use Python for ML/AI services and TypeScript around it, on AWS and PostgreSQL.Statistics you can defend. Experimental design, causal inference, measuring the real effect of an action — not just correlations. You know when a result is real, when it’s noise, and how to test it.Experimentation. You’ve designed, run and interpreted A/B tests or bandits on live traffic, and shipped the winner.You turn models into decisions. You can explain to stakeholders why the model says to call this client at 6pm — and defend it.🤝 What we offer💰 Salary at the top of the benchmark.📈 Fair equity with enormous upside potential.🧩 Real Ownership - Murphy's strategy is yours to drive.🙌 Small team, high autonomy, and outsized impact.🗣️ The founding team's direct attention, and a category with a $300B+ industry behind it.🛜 Hybrid & Flexible: Our default setup is hybrid – 3 days a week at our office and 2 days of remote work.📚 Our Process1️⃣ First Interview – Getting to Know YouA conversation with a future teammate who’s excited to find a new colleague. We’ll talk about your story, what drives you, and what you’re looking for next—no trick questions, just a genuine exchange.2️⃣ Second Interview – Deep DiveYou’ll meet the Hiring Manager and potentially another team member. This is a more technical discussion where we explore your skills in detail, walk through real scenarios, and answer any questions you might have about the role.3️⃣ Tech Assessment or Business CaseA practical exercise to see how you approach challenges similar to those you’d tackle at Murphy. You’ll have time to reflect and showcase your thinking—no rush, no surprises.4️⃣ Call with the FoundersOur founders meet every team member and it’s a great opportunity for you to learn about the company and its direction.👉 To learn more about how we hire and what to expect at every step, feel free to explore our Hiring Guide!👉 We are committed to building a diverse, inclusive, and equitable workplace where everyone, regardless of background, identity, or experience, feels valued and empowered to thrive. We believe that different perspectives drive innovation and success, and we actively foster an environment where all voices are heard and respected.

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.

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.