TensorFlow Jobs in UAE

<ul><li>Architect and implement scalable AI solutions on Azure, leveraging services like Azure Machine Learning, Azure OpenAI, and Azure Databricks.</li><li>Lead the design and development of complex AI models, including LLMs, computer vision, and natural language processing, tailored for specific business needs.</li><li>Drive the integration of AI capabilities into existing enterprise applications and workflows, ensuring seamless deployment and adoption.</li><li>Optimize AI models for performance, cost-efficiency, and reliability within the Azure cloud environment.</li><li>Mentor junior developers and data scientists, fostering a culture of innovation and best practices in AI development.</li><li>Collaborate with product managers and stakeholders to translate business requirements into robust AI solutions.</li><li>Stay abreast of the latest advancements in AI research and Azure AI services, proactively identifying opportunities for innovation.</li><li>Develop and maintain CI/CD pipelines for AI models, ensuring automated testing, deployment, and monitoring.</li><li>Troubleshoot and resolve complex technical issues related to AI model performance and Azure infrastructure.</li><li>Contribute to the development of reusable AI components and frameworks to accelerate future project delivery.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>8+ years of professional software development experience, with at least 3 years focused on AI/ML solutions.</p></li><li><p>Proven expertise in developing and deploying machine learning models using Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).</p></li><li><p>Hands-on experience with Azure AI services, including Azure Machine Learning, Azure OpenAI, Azure Cognitive Services, and Azure Databricks.</p></li><li><p>Strong understanding of MLOps principles and tools for model lifecycle management.</p></li><li><p>Excellent problem-solving skills and the ability to architect complex, scalable AI systems.</p></li><li><p>Proficiency in cloud-native development practices and containerization technologies (e.g., Docker, Kubernetes).</p></li><li><p>Exceptional communication and collaboration skills, with the ability to explain technical concepts to non-technical audiences.</p></li><li><p>Experience working in a fast-paced, agile development environment.</p></li><li><p>Familiarity with data engineering principles and working with large datasets.</p></li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Cntxt.AI, a leading technology company in the staffing and recruiting industry, is seeking a talented Applied Scientist to join our dynamic team.<br> As an Applied Scientist at Cntxt.<br>AI, you will have the opportunity to work on cutting-edge projects that leverage artificial intelligence and machine learning to revolutionize talent acquisition.<br> This role offers a unique blend of research and development, where you will directly impact the future of recruiting by designing and implementing innovative solutions.<br> If you are passionate about utilizing data-driven approaches to solve complex challenges and thrive in a collaborative environment, we invite you to apply and be part of our mission to reshape the staffing industry.<br> Responsibilities Develop and implement machine learning models to enhance candidate matching algorithms.<br> Analyze large datasets to extract valuable insights and drive data-driven decision-making.<br> Collaborate with cross-functional teams to design and deploy scalable solutions for recruitment processes.<br> Conduct research on new techniques and technologies to improve the efficiency of our AI-driven systems.<br> Optimize algorithms for performance and accuracy, continuously iterating and refining models.<br> Contribute to the development of innovative tools and features that advance Cntxt.<br>AI's competitive edge.<br> Participate in technical discussions and present findings to stakeholders in a clear and concise manner.<br> Master's or Ph.<br>D. in Computer Science, Statistics, Mathematics, or a related field.<br> Solid background in machine learning, data mining, and natural language processing.<br> Proficiency in programming languages such as Python, R, or Java.<br> Experience working with data processing frameworks like TensorFlow, PyTorch, or Spark.<br> Strong analytical skills and the ability to translate business requirements into technical solutions.<br> Excellent communication skills with the capacity to collaborate effectively in a team environment.<br> A passion for innovation and a drive to stay current with advancements in AI and ML technology.<br></span> </div>

<p>We are looking for a hands-on full stack developer to help build and improve a detection software system with multiple features such as detection, classification, and counting objects from 3D point cloud data end to end. This is a full-time, on-site Software Engineer/developer role based in Al Ain , United Arab Emirates. Daily responsibilities include implementing back-end services and APIs, writing clean and testable code, integrating software with hardware and third-party platforms, and troubleshooting issues in production environments. The role involves collaborating with cross-functional teams, contributing to system to technical documentation, and participating in code reviews and continuous improvement initiatives. The Software Engineer/developer will also help ensure that solutions remain secure, scalable, and aligned with client requirements and industry standards.</p><p>Responsibilities: • Build and maintain the LiDAR pipeline in Go and Python. • Develop and improve object detection, classification, and counting. • Build the React.js dashboard for visualizing point clouds and results. • Optimize the pipeline for speed, accuracy, and reliability. • Write clean, tested code and help shape technical decisions. Qualifications needed : • Strong, practical experience with Go and Python. • Solid experience building web interfaces with React.js. • Working knowledge of computer vision or 3D / point cloud data. • Ability to do basics of software analysis • Understanding of object detection and classification techniques. • Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience. • Strong problem-solving abilities, attention to detail, and the capacity to work effectively in a diverse, on-site team environment. • Good written and verbal communication skills in English; knowledge of Arabic is a plus. Nice to Have: • Experience with LiDAR or other sensor data. • Experience with ML frameworks such as PyTorch or TensorFlow. • Experience with point cloud tools such as PCL or Open3D. • Familiarity with AI coding assistants such as Claude Code.</p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><ul><li><p>Develop, train, and optimize machine learning models for classification, regression, forecasting, clustering, NLP, and deep learning use cases.</p></li><li><p>Build AI-driven solutions such as recommendation engines, anomaly detection systems, predictive scoring models, and generative AI applications.</p></li><li><p>Perform end‑to‑end data science workflows including data acquisition, cleaning, feature engineering, model selection, validation, and deployment.</p></li><li><p>Collaborate with data engineers to design scalable data pipelines and ensure high‑quality data availability for modelling.</p></li><li><p>Implement MLOps practices such as model versioning, monitoring, retraining, and performance tracking.</p></li><li><p>Conduct statistical analysis, experiment design, and A/B testing to validate model effectiveness and business impact.</p></li><li><p>Work with cloud platforms (Azure, AWS, or GCP) to train, deploy, and operationalize ML models.</p></li><li><p>Communicate insights, model results, and recommendations to technical and non‑technical stakeholders through dashboards, reports, and presentations.</p></li><li><p>Integrate models into business applications using APIs, cloud services, or automation frameworks.</p></li><li><p>Stay updated on emerging AI/ML technologies, LLMs, and best practices to continuously improve modeling approaches.</p></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li><p>Strong proficiency in Python and ML libraries such as Pandas, NumPy, Scikit‑learn, TensorFlow, or PyTorch.</p></li><li><p>Solid understanding of machine learning algorithms, statistical modeling, and model evaluation techniques.</p></li><li><p>Experience with SQL and working with relational databases.</p></li><li><p>Familiarity with cloud ML platforms such as Azure ML, AWS SageMaker, or Google Vertex AI.</p></li><li><p>Knowledge of MLOps tools and practices including MLflow, Kubeflow, or CI/CD pipelines.</p></li><li><p>Experience working with large datasets and distributed computing frameworks such as Spark or Databricks.</p></li><li><p>Strong data visualization and communication skills using Power BI, Tableau, or Python visualization libraries.</p></li><li><p>Understanding of NLP, deep learning architectures, and generative AI concepts.</p></li><li><p>Ability to translate business problems into analytical solutions and measurable KPIs<br><br><strong>Certification</strong><br>Microsoft PL-300: Power BI Data Analyst Certification<br>Any Cloud Certificate<br><br></p></li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <strong>Role Summary</strong> <p>An experienced Senior Robotics Perception Engineer is required to lead the development of advanced perception capabilities for autonomous systems. This role focuses on building robust, real-time perception solutions that enable reliable operation in complex and dynamic environments. In addition to hands-on technical contributions, the position involves guiding less experienced engineers and influencing system-level design decisions.</p><br><br> <strong>Key Responsibilities</strong> <ul> <li>Architect and develop perception algorithms that enhance environmental understanding, including object detection, tracking, terrain analysis, and scene interpretation </li><li>Own the full lifecycle of critical perception components, from initial concept through implementation, optimization, and deployment </li><li>Write efficient, production-grade C++ code with a strong focus on performance, reliability, and real-time execution </li><li>Collaborate with cross-functional engineering stakeholders to ensure seamless integration with localization, motion planning, and control systems </li><li>Plan and execute comprehensive testing strategies, including real-world validation, to ensure consistent system performance under varying operational conditions </li><li>Provide mentorship and technical guidance to junior engineers, supporting their growth and promoting engineering best practices </li><li>Contribute to system architecture decisions, ensuring scalability, maintainability, and alignment with overall platform design </li></ul> <strong>Required Qualifications</strong> <ul> <li>Bachelor’s or Master’s degree in Robotics, Computer Vision, Engineering, or a related field </li><li>Minimum of 7 years of experience in perception systems, computer vision, or autonomous technologies </li><li>Advanced proficiency in C++ with a strong track record of building and deploying high-performance systems </li><li>Hands-on experience with robotics middleware such as ROS (ROS1 or ROS2) </li><li>Deep knowledge of perception frameworks and libraries, such as OpenCV, PCL, or Open3D </li><li>Practical experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow), including real-time optimization techniques </li><li>Strong understanding of perception challenges such as multi-sensor fusion, point cloud processing, object tracking, and sensor calibration </li><li>Experience working with multiple sensor types, particularly LiDAR and camera systems </li></ul> <strong>Preferred Experience</strong> <ul> <li>Prior ownership of large-scale perception modules or major technical initiatives </li><li>Experience working with perception systems in complex, unstructured environments </li><li>Familiarity with deploying and optimizing models on embedded or edge platforms (e.g., ARM-based systems or GPU-accelerated devices) </li><li>Experience with containerization, deployment pipelines, and modern software engineering practices </li></ul> <strong>Candidate Profile</strong> <ul> <li>Strong analytical thinker with a hands-on, solution-oriented mindset </li><li>Comfortable working independently while contributing to broader system goals </li><li>Effective communicator capable of articulating complex technical concepts clearly </li><li>Passionate about mentoring and fostering knowledge sharing within engineering teams </li><li>Driven to deliver reliable, high-quality solutions in fast-paced development environments </li></ul> <br><br> </div>

<ul><li><p>AI & ML Engineering</p><ul><li><p>Develop, deploy, and optimize machine learning and deep learning models.</p></li><li><p>Build AI solutions for NLP, computer vision, predictive analytics, and intelligent automation.</p></li><li><p>Integrate AI services into enterprise applications and internal platforms.</p></li></ul><p>Generative AI</p><ul><li><p>Develop LLM-based applications, AI copilots, and RAG solutions.</p></li><li><p>Implement prompt engineering, model evaluation, embeddings, and semantic search.</p></li><li><p>Optimize model performance, scalability, and cost.</p></li></ul><p>Agentic AI</p><ul><li><p>Design and deploy autonomous and multi-agent AI systems.</p></li><li><p>Develop agent orchestration, planning, reasoning, memory, and tool integration.</p></li><li><p>Implement human-in-the-loop approvals and enterprise workflow automation.</p></li></ul><p>AI Operations (MLOps / LLMOps / AgentOps)</p><ul><li><p>Build CI/CD pipelines for AI models and agents.</p></li><li><p>Monitor AI systems for performance, drift, hallucinations, security, and reliability.</p></li><li><p>Manage model versioning, deployment, observability, and lifecycle operations.</p></li></ul><p>AI Governance & Responsible AI</p><ul><li><p>Implement AI governance, model risk management, and Responsible AI practices.</p></li><li><p>Maintain model documentation, validation, audit readiness, and compliance.</p></li><li><p>Ensure fairness, traceability, maintainability, privacy, and regulatory adherence.</p></li></ul><p>Agent Governance & Security</p><ul><li><p>Govern AI agent lifecycle, identity, access, and runtime controls.</p></li><li><p>Implement guardrails, audit logging, and secure integration with enterprise systems.</p></li><li><p>Protect AI solutions against prompt injection, data leakage, and adversarial attacks.</p></li></ul><p>Collaboration</p><ul><li><p>Work with business, engineering, security, and architecture teams to deliver AI solutions.</p></li><li><p>Mentor team members and promote AI engineering standards and best practice</p></li></ul></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>AI & Machine Learning</p><ul><li><p>Machine Learning, Deep Learning, NLP, Computer Vision</p></li><li><p>Predictive Analytics, Feature Engineering, Model Optimization</p></li></ul><p>Generative AI</p><ul><li><p>Large Language Models (LLMs)</p></li><li><p>Retrieval-Augmented Generation (RAG)</p></li><li><p>Prompt Engineering</p></li><li><p>Embeddings and Semantic Search</p></li><li><p>Fine-tuning Foundation Models</p></li></ul><p>Agentic AI</p><ul><li><p>Autonomous and Multi-Agent Systems</p></li><li><p>Agent Orchestration</p></li><li><p>Planning and Reasoning</p></li><li><p>Memory Management</p></li><li><p>Tool Calling</p></li><li><p>Human-in-the-Loop (HITL)</p></li><li><p>Model Context Protocol (MCP)</p></li></ul><p>Frameworks & Libraries</p><ul><li><p>PyTorch</p></li><li><p>TensorFlow</p></li><li><p>Scikit-learn</p></li><li><p>Hugging Face</p></li><li><p>LangChain</p></li><li><p>LangGraph</p></li><li><p>LlamaIndex</p></li><li><p>AutoGen</p></li><li><p>CrewAI</p></li><li><p>Semantic Kernel</p></li></ul><p>Cloud & Infrastructure</p><ul><li><p>Microsoft Azure AI Foundry</p></li><li><p>Azure Machine Learning</p></li><li><p>AWS Bedrock</p></li><li><p>Amazon SageMaker</p></li><li><p>Google Vertex AI</p></li><li><p>Docker</p></li><li><p>Kubernetes</p></li><li><p>Terraform</p></li></ul><p>Data & Integration</p><ul><li><p>SQL</p></li><li><p>PostgreSQL</p></li><li><p>MongoDB</p></li><li><p>Apache Spark</p></li><li><p>Vector Databases</p></li><li><p>REST APIs</p></li><li><p>FastAPI</p></li></ul><p>AI Operations</p><ul><li><p>MLflow</p></li><li><p>Kubeflow</p></li><li><p>Azure ML Pipelines</p></li><li><p>GitHub Actions</p></li><li><p>Azure DevOps</p></li></ul><p>AI Monitoring & Observability</p></li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><strong>Location:</strong> Abu Dhabi, UAE</p><br><br> <p>Our client is a leading artificial intelligence organisation focused on building secure, enterprise-grade AI solutions that help businesses and governments solve complex, real-world challenges.</p><br><br> <p>They specialise in developing cutting-edge applications powered by advanced AI technologies, enabling knowledge workers and organisations to unlock the full potential of large-scale data and automation.</p><br><br> <p>With a strong focus on innovation, research, and responsible AI development, the company is dedicated to delivering impactful solutions across multiple sectors.<br> <br> As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and deploying machine learning systems that power next-generation AI products.</p><br><br> <p>You will work closely with cross-functional teams to translate business requirements into scalable, production-grade AI solutions, particularly in the area of Generative AI and LLM-based systems.<br> <br> <strong>Key Responsibilities</strong></p><br><br> <br> <ul> <li>Model Development: Build, train, and deploy machine learning models to support advanced AI applications </li><li>Generative AI: Work with cutting-edge technologies including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) </li><li>System Design: Translate business use cases into scalable ML and AI solutions </li><li>Model Optimisation: Monitor performance, evaluate outputs, and continuously improve models in production </li><li>Data Pipelines: Design and maintain robust data pipelines to ensure high-quality inputs for ML models </li><li>Collaboration: Partner with engineering, product, and business teams to deliver impactful solutions </li></ul> <br> <strong>Requirements:</strong> <ul> <li> <p>5+ years’ experience in Machine Learning, Data Science, or related fields</p><br><br> </li><li> <p>Strong experience working with LLMs and fine-tuning techniques</p><br><br> </li><li> <p>Proficiency in Python (or similar programming languages)</p><br><br> </li><li> <p>Hands-on experience with ML frameworks such as:</p><br><br> <ul> <li>PyTorch </li><li>TensorFlow </li><li>scikit-learn </li></ul> </li><li> <p>Experience with Generative AI tools and frameworks, such as:</p><br><br> <ul> <li>LangChain </li><li>LlamaIndex </li><li>LangGraph </li><li>Vector databases (e.g. Weaviate) </li></ul> </li><li> <p>Proven track record of building production ML systems and solving real-world problems</p><br><br> </li><li> <p>Experience designing data pipelines and ML infrastructure</p><br><br> </li><li>Strong communication skills and ability to work across teams </li><li> Master’s or PhD in Computer Science, AI, Data Science, Statistics, or related field (preferred)<br> </li></ul> &nbsp;<br> <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Senior Manager - Artificial Intelligence</p><br> <br><br><br><p><span><b>THIS IS WHERE INCREDIBLE GROWTH BEGINS</b></span></p><br><br><p><span><b>Technology &amp; Infrastructure&nbsp;</b></span></p><br><br><p><span><b>Senior Manager – Artificial Intelligence</b></span></p><br><br><p><span>The team is doubling the size of our business. At the same time, they’re keeping maintenance costs down and driving asset capability up. With full responsibility for assets from creation to disposal, their watchword is reliability. Better still, they make sure we don’t just do what we legally need to do, but go further. So, we’ll embrace your fresh ideas to improve our use of energy and environmental resources. It’s all about meaningful change.</span></p><br><br><p><span><b>What you'll deliver</b></span></p><br><br><p><span>·</span><span>You’ll design, develop, and deploy cutting-edge AI solutions to solve complex business challenges and drive innovation across the organization.</span></p><br><br><p><span>·</span><span>You’ll establish and operationalize AI assurance frameworks, ensuring all AI initiatives meet standards for ethics, risk, compliance, and enterprise governance.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll ensure AI models are robust, scalable, secure, and production-ready, with strong lifecycle management, documentation, and traceability</span></p><br><br><p><span>·</span><span>You’ll define standards for model validation, testing, and continuous monitoring, ensuring performance, accuracy, fairness, and explainability</span></p><br><br><p><span>·</span><span>You’ll collaborate with data scientists, engineers, product teams, and stakeholders to deliver AI-driven products and services.</span></p><br><br><p><span>·</span><span>You’ll support enterprise AI strategy, advising on advanced AI, automation, and emerging technologies, while aligning with operational and commercial goals.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll engage with senior stakeholders and governance bodies, providing insights on AI risk, ethics, and assurance outcomes.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll work with Legal, Risk, Cybersecurity, and Compliance teams to ensure integrated and defensible AI decision-making.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll act as a thought leader, providing guidance, mentorship, and training on AI governance and best practices across the organization.&nbsp;</span></p><br><br><p><span><b>What you bring</b></span></p><br><br><p><span>·</span><span>You’ll have a Bachelor’s degree or higher in computer science, Engineering or related field with atleast 7-10 years of relevant experience in&nbsp;</span><span>in AI, machine learning, or data science.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll have proven experience developing and deploying AI models using tools such as TensorFlow, PyTorch, or similar frameworks.&nbsp;</span></p><br><br><p><span>·</span><span>You’ll have strong programming capability (e.g., Python, Java, C++) and deep understanding of ML techniques and algorithms</span></p><br><br><p><span>·</span><span>You’ll have strong understanding of Responsible AI, governance, and risk frameworks as well as excellent stakeholder management and communication skills, with the ability to translate complex concepts into business impact.&nbsp;</span></p><br><br><p><span><b>Life at Dubai Airports</b></span></p><br><br><p><span>Fast-moving and fast-growing, Dubai Airports is a business that’s all about delivering great airport experiences, 24 hours a day. Life here means always pushing – and being pushed – to work better and smarter. With us, you’ll be encouraged to be the best you can be. You’ll be part of the team that connects the world. And at every opportunity, you’ll go beyond; delivering an advanced, innovative future for yourself and our business, and making an impact that delivers for Dubai.</span></p><br><br> </div>

<p>We are looking for a senior Python developer with real depth in data science and machine learning, and the confidence to lead both a team and a client conversation. You will take business problems that arrive vague and turn them into models that ship, then keep them running well in production.<br>This is a hands-on role with ownership attached. You will design and deploy models, guide a small team through delivery, and explain what the results mean to people who do not think in confusion matrices.<br><strong>Key responsibilities</strong></p><ul><li><p>Lead the design, development and deployment of AI/ML models against real business problems</p></li><li><p>Apply statistical modelling, machine learning, deep learning and NLP as the problem demands</p></li><li><p>Build and maintain scalable data pipelines and model APIs, integrated into Python and Django applications</p></li><li><p>Own the project lifecycle end to end: data discovery, feature engineering, model evaluation and productionisation</p></li><li><p>Translate business requirements into analytical solutions and present findings to stakeholders and clients</p></li><li><p>Lead client interactions, requirement discussions and solution presentations</p></li><li><p>Mentor junior data scientists and engineers, and review deliverables for quality and consistency</p></li><li><p>Work with cross-functional teams to identify and prioritise data science initiatives</p></li><li><p>Ensure quality control, performance tuning and compliance across deployed models and services</p></li><li><p>Track developments in AI/ML and bring the ones worth having into the team.</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>Strong Python across data analysis, machine learning and back-end development</p></li><li><p>Proven experience developing and deploying ML models, not just prototyping them</p></li><li><p>Django experience, including integrating ML models with web applications</p></li><li><p>Command of libraries such as scikit-learn, TensorFlow, PyTorch and Keras</p></li><li><p>Expertise in data wrangling, statistical analysis, feature engineering and model tuning</p></li><li><p>REST APIs, SQL and NoSQL databases, and at least one cloud platform (AWS, GCP or Azure)</p></li><li><p>Git, Docker and CI/CD pipelines</p></li><li><p>Track record of client communication, requirement gathering and delivery</p></li><li><p>Excellent written and verbal communication, including the ability to explain technical concepts to non-technical audiences</p></li></ul><p><strong>Nice to have</strong></p><ul><li><p>Working knowledge of LLMs and their practical applications</p></li><li><p>Big data tools such as Spark, Hadoop or Kafka</p></li><li><p>Exposure to MLOps practices and tooling.</p></li></ul>

<ul><li>Design and implement machine learning algorithms tailored to solve specific business challenges, ensuring they align with project goals.</li><li>Collaborate with data scientists and analysts to preprocess and analyze large datasets, deriving actionable insights for model improvement.</li><li>Optimize and fine-tune existing AI models to enhance performance and accuracy, using state-of-the-art techniques and tools.</li><li>Conduct thorough testing and validation of AI models, ensuring robustness and reliability before deployment in production environments.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory Azure AI Services: Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks. Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI). LLM & Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques. ML Libraries & Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK). Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone. DevOps/MLOps: Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights. Cloud Security & Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns. AI Ethics & Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems. KNOWLEDGE, SKILLS, & EXPERIENCE Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred. Minimum Experience: 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments. Mandatory hands-on experience with Microsoft Azure AI Services. Experience working with large-scale datasets and real-time enterprise data. Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.</p></li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Job description <p>​</p><br><p>We are looking for a Senior Tech Lead with exceptional depth in AI, data systems, and product innovation.</p><br><p>This is not a traditional software engineering management role. We are seeking a world-class thinker and builder who is passionate about challenging legacy incumbents, leading deep technical exploration, and shipping real products that change the game.<br></p><br><p>You will lead forward-looking R&amp;D efforts, explore and prototype breakthrough ideas, and set the technical direction as this company scales across the MENA region. Working directly with the founders, you’ll have a primary voice in shaping not only <i>what </i>we build, but <i>how </i>we think.</p><br><p><br><b>Discover the Role</b></p><br><ul><li><p>Lead Technical Innovation: Identify whitespace opportunities, challenge legacy solutions, and architect future-ready systems for credit intelligence.</p><br></li><li><p>Prototype &amp; Build: Translate abstract concepts into high-impact prototypes and production-grade systems using AI and real-time data infrastructure.</p><br></li><li><p>Set Technical Direction: Own the architectural roadmap and strategic vision for R&amp;D initiatives with autonomy and clarity.</p><br></li><li><p>Push the Edge: Evaluate and apply emerging techniques in foundation models, causal inference, streaming analytics, and real-time ML.</p><br></li><li><p>Collaborate Across Disciplines: Partner with product, design, data science, and executive leadership to align technical innovation with strategic goals.</p><br></li><li><p>Mentor &amp; Elevate: Raise the bar for engineering and research excellence while building and scaling a high-performing team around you.</p><br></li></ul><p><br><b>Discover the Responsibilities </b></p><br><ul><li><p>You’ve led complex, high-impact engineering or AI projects at companies known for technical excellence (Big Tech, top-tier AI labs, or venture-backed startups).</p><br></li><li><p>You possess a strong grasp of the math, the models, and their practical application to real-world systems.</p><br></li><li><p>You are an active individual contributor who codes daily, prototypes rapidly, and understands systems at scale.</p><br></li><li><p>You combine vision with execution—you don’t just rebuild what’s been done, you imagine what’s possible.</p><br></li><li><p>You’ve worked across the full stack—from data infrastructure and backend systems to deploying ML models in production.</p><br></li><li><p>You thrive in ambiguous environments and operate with a bias toward bold action and continuous iteration.</p><br></li></ul><p><br><b>Discover the Requirements</b></p><br><ul><li><p>8+ years of engineering experience, with a strong track record of leading innovation in AI or data-intensive products.</p><br></li><li><p>Hands-on expertise with Python, distributed data systems (e.g., Spark, Kafka, Snowflake, Databricks), and ML frameworks (e.g., PyTorch, TensorFlow).</p><br></li><li><p>Proven experience architecting, deploying, and scaling production-grade systems.</p><br></li><li><p>Demonstrated ability to think creatively, challenge conventions, and lead R&amp;D from 0 to 1.</p><br></li><li><p>Deep understanding of the current AI research landscape and how to translate cutting-edge research into working software.</p><br></li></ul><br> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><ul><li><p>As the AI Engineer at the Bank within the Data Analytics &amp; Artificial Intelligence division, you will design, develop, and deploy production-grade AI solutions using Microsoft Azure AI Services and Python. Your focus will be on advancing the bank's capabilities in Generative AI, Agentic AI, intelligent automation, knowledge search, and content summarization by building scalable, secure, reliable, and responsible AI systems that enhance operational efficiency, customer engagement, and decision intelligence across the Group. The AI Engineer will work closely with Data Scientists, Platform Engineers, DevOps/MLOps Engineers, Business Analysts, and product teams to deliver end-to-end AI solutions. The role is critical for driving the organization's digital transformation agenda, empowering business users with advanced AI-powered tools, and improving operational efficiency through intelligent automation using GERNAS OS platform and Agent Development Kit (ADK).</p></li></ul><br><p>Role Overview: The position is a Level 1 technical support role focused on laptop configuration, delivery, and post-implementation support for applications like Outlook and Teams. </p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li><p>Experience &amp; Skills: Candidates should have 1-2 years of experience, but a relevant certification and foundational knowledge of desktop/laptop troubleshooting are essential Knowledge of Bloomberg and in-depth of audio-visual devices. Setting up a meeting room from Scratch TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory Azure AI Services: Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks. Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI). LLM &amp; Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques. ML Libraries &amp; Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK). Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone. DevOps/MLOps: Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights. Cloud Security &amp; Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns. AI Ethics &amp; Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems. </p></li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> The successful candidate will be responsible for developing end-to-end perception pipelines, optimizing machine learning models for edge deployment, and ensuring reliable performance under challenging conditions such as occlusion, varying lighting, motion, environmental interference, and complex multi-object scenarios. Key Responsibilities <ul> <li>Design, develop, train, and optimize computer vision and machine learning models for object detection, classification, recognition, and tracking. </li><li>Develop robust multi-object tracking and re-identification solutions capable of maintaining continuity through occlusions, rapid movement, environmental challenges, and sensor variations. </li><li>Create object selection, prioritization, and decision-making algorithms for complex scenes containing multiple targets or points of interest. </li><li>Optimize machine learning models for deployment on embedded and edge computing platforms, ensuring efficient operation within real-time processing and resource constraints. </li><li>Define, monitor, and improve key performance indicators including detection accuracy, tracking stability, false alarm rates, response latency, and target reacquisition performance. </li><li>Develop and maintain data collection, annotation, augmentation, and dataset management processes to support model development and continuous improvement. </li><li>Build simulation, validation, and testing environments to evaluate algorithm performance across diverse operational scenarios. </li><li>Design interfaces between perception components and downstream software systems, ensuring accurate transfer of object state information, confidence metrics, timestamps, and spatial data. </li><li>Support system integration, verification, validation, and performance testing activities. </li><li>Conduct root-cause investigations, performance analysis, and model tuning to address edge cases and challenging operating conditions. </li><li>Research and evaluate emerging computer vision, machine learning, and artificial intelligence techniques to improve system capabilities. </li><li>Produce technical documentation covering algorithms, model architecture, performance results, validation activities, limitations, and deployment strategies. </li></ul> Requirements <ul> <li>Strong proficiency in Python and C++ with extensive experience developing production-quality software applications. </li><li>Deep knowledge of computer vision, machine learning, and deep learning methodologies. </li><li>Hands-on experience with object detection, object classification, segmentation, and multi-object tracking algorithms. </li><li>Strong experience with modern deep learning frameworks such as PyTorch, TensorFlow, or equivalent technologies. </li><li>Experience optimizing and deploying machine learning models on embedded, edge, GPU-accelerated, FPGA-based, or specialized AI hardware platforms. </li><li>Working knowledge of image processing techniques including image enhancement, denoising, stabilization, super-resolution, and feature extraction. </li><li>Familiarity with multiple sensor technologies, including visible-light, thermal, infrared, and other imaging systems. </li><li>Experience evaluating model performance using quantitative metrics and validation methodologies. </li><li>Understanding of real-time perception systems and low-latency processing requirements. </li><li>Experience with software development best practices, including version control, testing frameworks, continuous integration, and code reviews. </li><li>Strong analytical, troubleshooting, and problem-solving capabilities. </li><li>Ability to work independently while collaborating effectively within multidisciplinary engineering environments. </li><li>Excellent written and verbal communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders. </li></ul> Qualifications <ul> <li>Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Robotics, Data Science, or a related technical discipline. </li><li>Minimum of 6 years of hands-on experience in computer vision, machine learning, artificial intelligence, or related fields. </li><li>Demonstrated experience developing and deploying real-world perception systems for robotics, automation, intelligent devices, industrial systems, autonomous platforms, or similar technology domains. </li><li>Strong understanding of end-to-end perception architectures, sensor integration, real-time data processing, and edge-computing environments. </li><li>Experience with large-scale dataset development, annotation workflows, model training pipelines, and performance optimization. </li><li>PhD in a relevant field is considered an advantage. </li></ul> Preferred Experience <ul> <li>Real-time object detection and tracking systems. </li><li>Multisensor and sensor-fusion applications. </li><li>Edge AI and embedded machine learning deployment. </li><li>Robotics, automation, intelligent systems, or autonomous technologies. </li><li>Performance optimization for low-latency and resource-constrained environments. </li><li>Large-scale machine learning model development and operational deployment. </li></ul> <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span> ' : - ( - ) Experience: 7+ yrs Location: Abu Dhabi, United Arab Emirates Job Type: Full-time We are seeking a Senior AI/ML Engineer to design, develop, and deploy production-grade AI and machine learning solutions for financial services use cases.<br> This is a hands-on role for an experienced professional with strong expertise in Python, Machine Learning, Generative AI, LLMs, RAG, Agentic AI, and Data Engineering .<br> The ideal candidate will be comfortable transforming complex business and financial requirements into scalable AI-powered applications.<br> You will work closely with finance, quantitative, technology, and business teams to develop practical solutions across areas such as risk, credit, compliance, treasury, markets, and financial reporting.<br> Key Responsibilities Design, develop, and deploy AI/ML and Generative AI solutions for financial services use cases.<br> Build LLM applications, RAG pipelines, AI agents, document intelligence solutions, and workflow automation tools .<br> Develop scalable Python-based APIs, model services, dashboards, and data pipelines.<br> Work with financial datasets, including transaction data, credit data, market data, financial statements, and unstructured documents.<br> Support AI solutions across risk management, credit, treasury, compliance, markets, corporate banking, and management reporting.<br> Prototype innovative AI solutions rapidly and transform successful prototypes into production-grade applications.<br> Design and implement solutions using technologies such as Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, FastAPI, Flask, Streamlit, LangChain, LangGraph, LlamaIndex, vector databases, embeddings, and RAG .<br> Build and integrate cloud-native solutions using Azure, AWS, or GCP , along with Docker, Kubernetes, Git, and CI/CD practices.<br> Collaborate with finance and quantitative teams to translate complex methodologies into practical software solutions.<br> Implement appropriate testing, logging, monitoring, security, and basic MLOps practices.<br> Work with cross-functional teams to understand business requirements and deliver scalable solutions.<br> Mentor junior engineers, developers, and analysts on coding standards, modelling practices, testing, and deployment.<br> What Makes You a Great Fit 7+ years of experience in AI/ML Engineering, Data Science, Software Engineering, or Analytics Engineering .<br> Strong hands-on expertise in Python and modern machine learning frameworks.<br> Proven experience building and deploying real-world AI/ML applications rather than working exclusively with notebooks or prototypes.<br> Strong understanding of LLMs, Generative AI, RAG, agentic workflows, NLP, embeddings, vector databases, or document intelligence .<br> Experience developing APIs, data pipelines, dashboards, and production-grade model services.<br> Familiarity with SQL, structured databases, cloud platforms, containers, CI/CD, testing, and deployment practices.<br> Strong problem-solving and analytical skills with the ability to work through ambiguous business challenges.<br> Ability to communicate effectively with both technical teams and finance/business stakeholders.<br> Exposure to banking, fintech, payments, insurance, asset management, consulting, or capital markets is highly valuable.<br> Knowledge of financial use cases such as credit risk, fraud, KYC, treasury, trading, portfolio analytics, regulatory reporting, or financial document processing is an advantage.<br> A practical, delivery-focused mindset with the ability to build solutions quickly and continuously improve them for production use.<br></span> </div>

<ul><li><p>Designing and building Generative AI applications using Large Language Models (LLMs)</p></li><li><p>Developing Agentic AI solutions, including autonomous agents, multi-agent orchestration, and workflow-driven decision systems</p></li><li><p>Building solutions using frameworks such as LangChain, LangGraph or similar agent frameworks</p></li><li><p>Implementing RAG architecture with vector databases</p></li><li><p>Knowledge of embeddings, vector DBs, and model evaluation.</p></li><li><p>Implement various Context Engineering strategies to reduce Token Utilization & Latency.</p></li><li><p>Implement RAG Strategies to reduce retrieval latency and answer relevancy.</p></li><li><p>Prompt engineering, tool calling, memory management, and agent orchestration</p></li><li><p>Integrating AI services with enterprise APIs, middle ware, and backend systems</p></li><li><p>Evaluated & Improvise AI Agent Performance using several metrics</p></li><li><p>Deploying scalable AI solutions on Azure / AWS cloud platforms</p></li><li><p>Working with model evaluation, guardrails, observability, and AI governance</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>Bachelor’s degree in computer science, Engineering, or a related field.</p></li><li><p>Senior professional with around 10 years of experience.</p></li><li><p>3+ years of relevant experience in AI Engineering</p></li><li><p>Working experience in an agile software development environment with a good understanding of the principles of agile architecture. Strong collaborative mindset for collective decentralized decision making.</p></li><li><p>Demonstrate strong technical skills with a deep understanding of modern architectural styles and practices such as Microservices, Containers, Cloud (AWS, Azure), APIs, Continuous Delivery, Event-driven architecture, Evolutionary architecture, etc., with a passion for hands on coding.</p></li><li><p>Strong foundation knowledge of software architecture concepts, patterns, principles, and quality attributes. Ability to consistently apply them in real-world scenarios with a pragmatic, system thinking, and problem-solving mindset by analyzing architecture trade-offs for delivering high-quality, sustainable solution architecture.</p></li><li><p>Proven leadership skills with a proactive, positive, and growth mindset. Ability to foster and motivate programmers for delivering with craftsmanship. Good personal skills to continuously engage and communicate with an egoless empathetic mindset.</p></li><li><p>Experience and expertise in delivering architecture for large software solutions meeting critical business purposes. Ability to proactively discover technical debts and continuous improvement opportunities of existing live systems. Work closely with the product owner and enterprise architects to influence and prioritize technical backlog items.</p></li><li><p>Strong proficiency in Python (NumPy, pandas, FastAPI, PyTorch/TensorFlow).</p></li><li><p>Experience with Agent framework LangChain, Lang Graph.</p></li><li><p>Architect end-to-end data indexing pipelines optimized for semantic search and RAG.</p></li><li><p>Design resilient data ingestion frameworks that ensure high availability and low latency for vectorized datasets.</p></li><li><p>Experience deploying and managing models via Amazon Bedrock, Azure OpenAI Service, and Google Vertex AI.</p></li><li><p>Integration of pre-built AI APIs for Speech-to-Text, Computer Vision, and Natural Language Processing (NLP).</p></li><li><p>Leveraging serverless architectures (e.g., AWS Lambda, Azure Functions) to trigger AI inference and data pre-processing.</p></li><li><p>Experience working with CI/CD tools like Jenkins/Gitlab in Cloud Native environments.</p></li><li><p>Experience in setting up pipeline for cloud based and on-prem based application with static code analysis, requirement tagging in Jira.</p></li><li><p>Experience working with one or more DevOps tools & config management tools.</p></li><li><p>Experience in managing and deploying AI workloads in Kubernetes.</p></li><li><p>Experience operating monitoring tools for traditional and cloud environments.</p></li><li><p>Strong analytical mind for problem solving.</p></li></ul>

<p>Job Purpose- • Strategic focus: Prioritizing PPD initiatives and projects with fixed timelines and budget that can be offloaded from core personnel onto contractors to enable core personnel to focus on strategic and operational objectives. • Service improvement: Timely and efficient delivery of specific PPD initiatives and projects with single point accountability. • Cost optimization through in-house and on-the-job knowledge and skills transfer from the implemented initiatives and projects without depending on external vendors. • Effective vendor and internal functional coordination based on expertise and focused collaboration with relevant stakeholders. Key Responsibilities- A. AI & Advanced Analytics: • Design and implement AI/ML models for production forecasting, anomaly detection, and optimization. • Develop predictive analytics for equipment reliability, deferment reduction, and hydrocarbon loss management. • Integrate AI solutions with real-time production systems and hydrocarbon accounting platforms. • Expertise in AI/ML frameworks (Python, TensorFlow, PyTorch). B. Business Intelligence (BI) Development: • Build and maintain BI dashboards for production planning, hydrocarbon accounting and allocation, and performance monitoring. • Automate reporting workflows using tools like Power BI, Tableau, Qlik, or similar. • Ensure dashboards provide actionable insights for operations, planning, financial and commercial teams. • Develop interactive data visualizations, dashboard creation and reporting automation for the budget (New systems, Department requirements, etc.) C. Data Management & Integration: • Oversee data acquisition from PHD, HEMS, DCS, systems, and hydrocarbon accounting systems (e.g., Energy Components, SAP IS-Oil). • Ensure data quality, integrity, and consistency across multiple sources. • Implement ETL processes and manage data pipelines for analytics and visualization. D Visualization & Decision Support: • Develop interactive visualizations for production trends, allocation breakdowns, and forecast accuracy. • Provide intuitive tools for management to analyze KPIs and make informed decisions. • Support scenario planning and “what-if” analysis for production optimization. E. Digital Transformation & Automation: • Drive initiatives for digital oilfield implementation and smart hydrocarbon accounting. • Automate manual processes in planning and reporting using AI and RPA (Robotic Process Automation). • Champion data-driven culture and train stakeholders on analytics tools. F. Governance & Compliance: • Ensure compliance with data security, regulatory reporting, and corporate standards. • Maintain audit trails for all data transformations and analytics outputs. G. Role-Specific / Best-Practice KPIs • Accuracy and reliability of AI-driven forecasts. • Reduction in manual reporting time through BI automation. • Improvement in decision-making speed and quality. • Data integrity and system uptime for analytics platforms.</p><p>Experience- More than 10 years of relevant experience. Technical Competencies- • Exposure to BI tools (Power BI, Tableau, Qlik). • Basic knowledge of data engineering (SQL, ETL processes). • Understanding of visualization and reporting techniques for technical and non-technical audiences. • Proficiency in MS Excel (charts, trend analysis) and MS Office tools. • Awareness of oil & gas production systems and digital transformation concepts • Familiarity with document management and reporting tools (MS Word, Adobe Acrobat). Working Schedule- • ADNOC normal working hours with weekends and holidays. • The project duration is 3 years, with an optional extension of an additional 2 years.</p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Brocode Solutions is seeking an experienced and innovative AI Engineer to lead the design, development, and deployment of cutting-edge AI solutions. The ideal candidate will have extensive experience in Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and intelligent chatbot development.</p><p>You will be responsible for building enterprise-grade AI applications, autonomous agents, knowledge retrieval systems, and AI-powered business automation solutions for clients across multiple industries</p><p>.</p><p><strong>Key Responsibilities</strong></p><br><ul><li><p>Design, develop, and deploy AI-powered applications using Large Language Models (LLMs).</p></li><li><p>Build intelligent AI Agents capable of planning, reasoning, tool usage, and workflow automation.</p></li><li><p>Develop and optimize Retrieval-Augmented Generation (RAG) systems using vector databases and enterprise knowledge bases.</p></li><li><p>Architect conversational AI solutions, chatbots, virtual assistants, and customer support automation platforms.</p></li><li><p>Fine-tune, evaluate, and optimize open-source and commercial AI models.</p></li><li><p>Integrate AI solutions with enterprise systems such as ERP, CRM, HRMS, and custom applications.</p></li><li><p>Build multi-agent systems and orchestrate complex AI workflows.</p></li><li><p>Implement prompt engineering, agent memory, tool calling, and function execution frameworks.</p></li><li><p>Develop scalable APIs and microservices for AI applications.</p></li><li><p>Collaborate with software engineering teams to deploy AI solutions in cloud and on-premise environments.</p></li><li><p>Monitor model performance, accuracy, hallucination rates, and AI system reliability.</p></li><li><p>Stay current with emerging AI technologies and industry best practices.</p></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"><br></p><p><strong>AI &amp; Machine Learning</strong></p><br><ul><li><p>7–10 years of software engineering experience with at least 4+ years focused on AI/ML.</p></li><li><p>Strong experience with Generative AI and Large Language Models (GPT, Claude, Gemini, Llama, Mistral, etc.).</p></li><li><p><strong>Hands-on experience building AI Agents using frameworks such as:</strong></p><ul><li><p>LangChain</p></li><li><p>LangGraph</p></li><li><p>CrewAI</p></li><li><p>AutoGen</p></li><li><p>LlamaIndex</p></li><li><p>Semantic Kernel</p><br></li></ul></li></ul><p><strong>RAG &amp; Knowledge Systems</strong></p><br><ul><li><p>Extensive experience designing and implementing RAG architectures.</p></li><li><p>Experience with vector databases:</p><ul><li><p>Pinecone</p></li><li><p>Weaviate</p></li><li><p>Qdrant</p></li><li><p>ChromaDB</p></li><li><p>Milvus</p></li><li><p>FAISS</p></li></ul></li><li><p>Knowledge of document processing, embeddings, chunking strategies, and semantic search.</p><br></li></ul><p><strong>Chatbots &amp; Conversational AI</strong></p><br><ul><li><p>Development of enterprise chatbots and virtual assistants.</p></li><li><p>Experience with conversational memory, context management, and multi-turn interactions.</p></li><li><p>Integration with WhatsApp, Microsoft Teams, Slack, Web, and Mobile platforms.</p></li></ul><p>Programming</p><ul><li><p>Expert-level Python development.</p><br></li><li><p><strong>Experience with:</strong></p><ul><li><p>FastAPI</p></li><li><p>Django</p></li><li><p>Flask</p></li><li><p>REST APIs</p></li><li><p>GraphQL</p><br></li></ul></li></ul><p><strong>Cloud &amp; DevOps</strong></p><br><ul><li><p>Experience with AWS, Azure, or Google Cloud.</p></li><li><p>Containerization using Docker and Kubernetes.</p></li><li><p>CI/CD pipelines and MLOps practices.</p></li><li><p>Model deployment and monitoring.</p><br></li></ul><p><strong>Databases</strong></p><br><ul><li><p>PostgreSQL</p></li><li><p>MongoDB</p></li><li><p>Redis</p></li><li><p>Elasticsearch</p><br></li></ul><p><strong>Preferred Qualifications</strong></p><br><ul><li><p>Experience building autonomous AI agents for business process automation.</p></li><li><p>Knowledge of multimodal AI systems (Text, Image, Audio, Video).</p></li><li><p>Experience with fine-tuning open-source LLMs.</p></li><li><p>Experience with AI security, governance, and compliance.</p></li><li><p>Familiarity with NLP, transformers, and deep learning frameworks such as PyTorch or TensorFlow.</p></li><li><p>Experience deploying AI solutions in enterprise environments.</p></li></ul><br><p><strong>What We Offer</strong></p><br><ul><li><p>Opportunity to work on cutting-edge AI and Generative AI projects.</p></li><li><p>Exposure to enterprise-scale AI implementations across UAE and GCC markets.</p></li><li><p>Collaborative and innovation-driven work environment.</p></li><li><p>Competitive salary and benefits package.</p></li><li><p>Career growth opportunities in emerging AI technologies.</p></li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Job Purpose<p><span>At Emirates Group our Analytics Centre of Excellence (ACoE) is a centralized unit that provides data and analytics support to Emirates Group businesses. This allows our businesses to make better decisions by using data and analytics to understand our customers, operations, and markets.The ACoE is an essential part of Emirates Group's digital transformation strategy. The unit is helping Emirates Group to become a more data-driven organization and to make better decisions by using data and analytics.</span></p><br><br><br><p><span>As a <strong>Data Scientist Team Lead </strong>you will manage and drive data science projects through the application of mathematical modelling, machine learning, problem structuring and big data analysis to solve complex business problems across the Emirates Group portfolio. The role will require strong skills in computer science, mathematics, statistics and creative problem solving. The job holder is a focused individual who is able to transcend the world of theory, bring it to life in the business context and collaborate successfully with cross functional teams including academic researchers, business stakeholders and information technology teams.</span></p><br><br><br><p><strong><span>In this role you will:</span></strong></p><br><br><ul><li><span>Manage team of Data Scientists, ensuring the culture, strategy and vision are passed to the teams. Aligned with the DS and EA leadership, review team capabilities and establish training/mentoring plan.</span></li><li><span>Support and drive DS execution within team, targeting and developing relationships with the key internal stakeholders and clients to continue to drive practice demand growth.</span></li><li><span>Derive business insight from large, structured, semi-structured and unstructured, data sets and work with business stakeholders to deploy insights derived from this analysis to extract commercial value.</span></li><li><span>Develop, formulate and execute big data models to solve complex business problems. Research, design, implement and validate cutting-edge algorithms to achieve targeted business outcomes using mathematical models, machine learning, operational research theories and dynamic simulations.</span></li><li><span>Build prescriptive models to identify multi-dimensional trends and patterns to understand our customers, optimise revenue and demand management plus drive efficiencies across the operational environment including aircraft operations, engineering, workforce management and catering.</span></li><li><span>Work with cross-functional team members, combining computer science and mathematics, to identify and inject high-value actionable insights into business processes at their point of highest impact. Work in quick iterations, using the techniques and algorithms best suited for solving the challenging problems of the aviation business.</span></li><li><span>Develop and recommend enhancements to existing tools with the goal of advancing the data science capabilities of the organisation. Perform validation and testing of models to ensure adequacy and reformulate models as necessary.</span></li><li><span>Clearly document and communicate the outcomes of the data science initiatives and make sure that the insights and findings can be clearly understood by business stakeholders and translated into actions.</span></li><li><span>Inspire and promote the adoption of advanced analytics and data science across the entirety of our organization and provide expertise on mathematical concepts for the broader applied analytics team.</span></li></ul><br>Qualification<p><span><strong><span>To be considered for the role, you must meet the below requirements: </span></strong></span></p><br><br><p><span><strong><span><u>Qualifications:</u></span></strong></span></p><br><br><ul><li><span>MSc/PhD in a relevant field such as data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning or economics.</span></li></ul><br><p><span><strong><span><u>Experience:</u></span></strong></span></p><br><br><ul><li><span>7-10+ years of hands-on experience in the Analytics ecosystem including:</span></li></ul><br><ol><li><ol><li><span>Experience Managing Data Science or Analytics Teams or acting as Manager in a consulting company.</span></li><li><span>3-5 years hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (Tensorflow, Keras, etc.).</span></li><li><span>5-7 years hands-on experience with SQL, R, Python.</span></li><li><span>2-4 years hands-on experience with DevOps frameworks (Git, CI/CD, Docker).</span></li><li><span>3-5 years hands-on experience building libraries and packages to be re-used by others.</span></li><li><span>3-5 years hands-on experience building DS Solutions for production usage.</span></li><li><span>Team player with a problem-solving attitude.</span></li><li><span>Experience of leading &amp; delivering advanced analytical projects to large, complex organisations in a multi-functional environment.</span></li><li><span>Able to challenge and review the quality and value generated from analytical output.</span></li><li><span>Focus on driving business value for business clients to support long term relationships. Ability to grow teams, ensuring the culture and strategy gets followed by the new hires.</span></li></ol></li></ol><br><p><span>Join us in a management role and enjoy an attractive tax-free salary. On top of our generous travel benefits, including discounted flights and hotel stays around the world, this managerial role also has an excellent leave and healthcare package. That’s on top of transport benefits, life insurance and more.</span></p><br><br>Salary &amp; benefits<p><span><span>Find out what it’s like to live and work in our fast-paced, cosmopolitan home city in the Dubai Lifestyle section of our website </span></span><span><span>www.emirates.com/careers</span></span></p><br><br><br> </div>

<p>We are looking for an experienced AI Engineer responsible for designing, developing, and deploying Generative AI and Agentic AI solutions that support enterprise-scale business use cases. This role includes building intelligent systems that integrate complex backend services and client-facing applications across web, mobile, and enterprise platforms. The primary responsibility will be to design and develop AI-powered applications, autonomous agents, and multi-agent workflows, while coordinating with cross-functional teams across architecture, engineering, product, and business functions. Thus, a commitment to collaborative problem solving, sophisticated design, and product quality is essential.</p><br><p><strong>KEY ACCOUNTABILITIES:</strong></p><ul><li><p>Designing and building Generative AI applications using Large Language Models (LLMs)</p></li><li><p>Developing Agentic AI solutions, including autonomous agents, multi-agent orchestration, and workflow-driven decision systems</p></li><li><p>Building solutions using frameworks such as LangChain, LangGraph or similar agent frameworks</p></li><li><p>Implementing RAG architecture with vector databases</p></li><li><p>Knowledge of embeddings, vector DBs, and model evaluation.</p></li><li><p>Implement various Context Engineering strategies to reduce Token Utilization & Latency.</p></li><li><p>Implement RAG Strategies to reduce retrieval latency and answer relevancy.</p></li><li><p>Prompt engineering, tool calling, memory management, and agent orchestration</p></li><li><p>Integrating AI services with enterprise APIs, middle ware, and backend systems</p></li><li><p>Evaluated & Improvise AI Agent Performance using several metrics</p></li><li><p>Deploying scalable AI solutions on Azure / AWS cloud platforms.</p></li><li><p><strong>Working with model evaluation, guardrails, observability, and AI governance</strong></p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>Bachelor's degree in Computer Science, Engineering, or a related field.</p></li><li><p>Senior professional with around 10 years of experience.</p></li><li><p>3+ years of relevant experience in AI Engineering</p></li><li><p>Working experience in an agile software development environment with a good understanding of the principles of agile architecture. Strong collaborative mindset for collective decentralized decision making.</p></li><li><p>Demonstrate strong technical skills with a deep understanding of modern architectural styles and practices such as Microservices, Containers, Cloud (AWS, Azure), APIs, Continuous Delivery, Event-driven architecture, Evolutionary architecture, etc., with a passion for hands on coding.</p></li><li><p>Strong foundation knowledge of software architecture concepts, patterns, principles, and quality attributes. Ability to consistently apply them in real-world scenarios with a pragmatic, system thinking, and problem-solving mindset by analyzing architecture trade-offs for delivering high-quality, sustainable solution architecture.</p></li><li><p>Proven leadership skills with a proactive, positive, and growth mindset. Ability to foster and motivate programmers for delivering with craftsmanship. Good personal skills to continuously engage and communicate with an egoless empathetic mindset.</p></li><li><p>Experience and expertise in delivering architecture for large software solutions meeting critical business purposes. Ability to proactively discover technical debts and continuous improvement opportunities of existing live systems. Work closely with the product owner and enterprise architects to influence and prioritize technical backlog items.</p></li><li><p>Strong proficiency in Python (NumPy, pandas, FastAPI, PyTorch/TensorFlow).</p></li><li><p>Experience with Agent framework LangChain, Lang Graph.</p></li><li><p>Architect end-to-end data indexing pipelines optimized for semantic search and RAG.</p></li><li><p>Design resilient data ingestion frameworks that ensure high availability and low latency for vectorized datasets.</p></li><li><p>Experience deploying and managing models via Amazon Bedrock, Azure OpenAI Service, and Google Vertex AI.</p></li><li><p>Integration of pre-built AI APIs for Speech-to-Text, Computer Vision, and Natural Language Processing (NLP).</p></li><li><p>Leveraging serverless architectures (e.g., AWS Lambda, Azure Functions) to trigger AI inference and data pre-processing.</p></li><li><p>Experience working with CI/CD tools like Jenkins/Gitlab in Cloud Native environments.</p></li><li><p>Experience in setting up pipeline for cloud based and on-prem based application with static code analysis, requirement tagging in Jira.</p></li><li><p>Experience working with one or more DevOps tools & config management tools.</p></li><li><p>Experience in managing and deploying AI workloads in Kubernetes.</p></li><li><p>Experience operating monitoring tools for traditional and cloud environments.</p></li><li><p><strong>Strong analytical mind for problem solving.</strong></p></li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <b>Overview:</b> <br><br><br><br><br><p><span><span>Analog is looking for an exceptional Principal Robotics Research Engineer to join our core robotics team. In this role, you will help setting the technical direction for our robotic systems research — spanning perception, state estimation, motion planning, and control — and translate fundamental advances into production-grade capabilities deployed on real hardware. You will act as a force-multiplier for the broader engineering organisation, driving both the science and the systems that bring intelligent robots to life.</span> </span></p><br><br><b>Responsibilities:</b> <br>Research Leadership &amp; Technical Direction<ul><li><p>Identify breakthrough opportunities across the robotics stack and emerging AI paradigms.</p><br><br></li><li><p>Translate research insights into impactful and feasible product roadmap initiatives.</p><br><br></li><li><p>Publish at leading conferences including ICRA, IROS, RSS, and CoRL, while driving patent innovation.</p><br><br></li></ul>Perception &amp; AI<ul><li><p>Architect multi-modal perception systems integrating vision, LiDAR, radar, depth, and acoustic sensing.</p><br><br></li><li><p>Lead research in 3D scene understanding, tracking, segmentation, and open-vocabulary recognition.</p><br><br></li><li><p>Develop foundation models and real-time AI architectures for robotic perception.</p><br><br></li></ul>State Estimation &amp; Sensor Fusion<ul><li><p>Design robust SLAM, visual-inertial odometry, and GPS/GNSS fusion systems.</p><br><br></li><li><p>Advance probabilistic and learning-based sensor fusion for resilient localisation.</p><br><br></li><li><p>Oversee calibration, synchronisation, validation, and benchmarking frameworks.</p><br><br></li></ul>Motion Planning &amp; Control<ul><li><p>Build planning frameworks for dynamic and unstructured environments.</p><br><br></li><li><p>Lead MPC, reinforcement learning, imitation learning, and safety-critical control research.</p><br><br></li><li><p>Drive trajectory optimisation and whole-body robotic motion generation.</p><br><br></li></ul>System Integration &amp; Deployment<ul><li><p>Own end-to-end integration of perception, planning, estimation, and control systems.</p><br><br></li><li><p>Establish engineering standards for latency, determinism, and fault tolerance.</p><br><br></li><li><p>Lead simulation, hardware-in-the-loop testing, and deployment optimisation for onboard compute systems.</p><br><br></li></ul><br><b>Qualifications:</b> <br><p>• PhD in Robotics Computer Science Electrical or Mechanical Engineering or equivalent research experience<br>• 10 plus years of robotics research and engineering across perception estimation planning or control<br>• Strong expertise in C plus plus Python ROS and ROS2 with real time safety critical systems experience<br>• Proven leadership managing high performing engineering or research teams<br>• Experience taking robotics solutions from prototype to field deployment<br>• Strong communication skills across technical product and executive stakeholders<br>• Experience with PyTorch TensorFlow JAX GPU compute and simulation platforms including Isaac Sim Gazebo and MuJoCo</p><br><br><br> </div>