224 Ml Engineer jobs in the United Arab Emirates

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BlackStone eIT, a leading computer software company, is looking for a skilled and motivated AI & ML Engineer to join our innovative team. In this role, you will be at the forefront of developing and implementing state-of-the-art artificial intelligence (AI) and machine learning (ML) algorithms to enhance our product offerings and optimize business functions. You will work collaboratively with data scientists, software engineers, and product teams to translate complex data into actionable insights and effective machine learning models.

Your expertise will play a pivotal role in driving data-driven decision-making within the organization. This is an exciting opportunity to work on high-impact projects that leverage the latest advancements in AI and ML technologies.

Requirements

• Proven experience as an AI & ML Engineer or in a related field, with at least 3 years of experience
• Strong understanding of machine learning algorithms, deep learning, natural language processing, and computer vision techniques
• Proficiency in programming languages such as Python, Java, or R
• Hands-on experience with ML frameworks and libraries (TensorFlow, Keras, PyTorch, etc.)
• Experience with data preprocessing, feature extraction, and model evaluation
• Background in statistics and mathematics to enhance algorithm performance
• Ability to work with large datasets and experience with big data technologies (Hadoop, Spark, etc.) is a plus
• Excellent problem-solving skills, attention to detail, and a collaborative attitude
• Strong verbal and written communication skills to convey technical concepts to non-technical stakeholders
• A degree in Computer Science, Mathematics, Data Science, or a related field is preferred
  
  

• Paid Time Off
• Performance Bonus
• Training & Development

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Information Technology
• Industries IT Services and IT Consulting

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Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates 6 days ago

Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates AED3,000.00-AED7, month ago

Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates 1 year ago

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About the job you are considering

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

• Model Configuration & Fine-Tuning: Design, implement, and optimize machine learning models by tailoring architecture and hyperparameters to meet specific project requirements. Employ advanced fine-tuning techniques to maximize model performance on specialized data sets, ensuring models are robust, efficient, and production ready.
• AML Pipeline Development: Architect, develop, and maintain automated machine learning (AML) pipelines that streamline data ingestion, preprocessing, model training, evaluation, and deployment. Utilize best practices to ensure scalability, modularity, and traceability in all pipeline components, enabling rapid experimentation and reproducibility.
• Accuracy Optimization: Apply state-of-the-art methodologies to optimize the accuracy and efficacy of machine learning solutions. Conduct comprehensive error analyses, implement advanced feature engineering, leverage transfer learning, and perform model ensembling to achieve superior predictive performance.
• Integration with Confidential Compute Pattern: Collaborate with security and cloud teams to ensure all AI/ML models are integrated with confidential computing environments. Safeguard sensitive data and model assets by designing privacy-preserving architectures using secure enclaves, federated learning, and encryption-in-use techniques.
• Collaboration & Stakeholder Engagement: Partner with business analysts, data scientists, engineers, and stakeholders to translate business objectives into actionable AI/ML solutions. Communicate complex technical concepts in a clear and accessible manner to both technical and non-technical audiences.
• Continuous Learning & Innovation: Stay abreast of the latest developments in AI/ML research, tools, and frameworks. Identify opportunities to incorporate cutting-edge techniques into project workstreams, fostering a culture of continuous improvement and innovation.

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a closely related field. PhD is a plus.
• Proven experience in configuring, fine-tuning, and deploying machine learning models (both supervised and unsupervised).
• Strong proficiency in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-Learn, Keras, and XGBoost.
• Hands-on experience with building and managing end-to-end AML pipelines using tools like Azure ML, MLflow, Kubeflow, or similar.
• Expertise in hyperparameter optimization, cross-validation, and model selection for maximizing accuracy.
• Solid understanding of security principles, especially in confidential computing, data encryption, and federated learning.
• Familiarity with cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes).
• Strong analytical and problem-solving skills with the ability to troubleshoot complex data and model issues.
• Excellent communication and presentation skills, with experience working in collaborative, multidisciplinary teams.
• Proactive, curious, and adaptable, with a continuous learning mindset.

• Experience implementing AI/ML solutions in regulated industries (e.g., finance, healthcare, government) where data privacy is paramount.
• Knowledge of secure multi-party computation, homomorphic encryption, or privacy-enhancing technologies.
• Exposure to MLOps, CI/CD for ML, and production-grade ML systems.
• Background in optimization algorithms, reinforcement learning, or generative models

We are looking for an AI/ML Engineer with at least 2 years of experience preferably in the real estate industry to develop and deploy AIdriven solutions. The ideal candidate will have expertise in machine learning data analysis and automation to enhance business processes optimize property listings and improve customer insights.
Key Responsibilities:

• Develop and train machine learning models for property valuation lead scoring and predictive analytics.
  
• Analyze real estate market trends and customer behavior using AIdriven insights.
  
• Optimize search and recommendation algorithms for property listings.
  
• Implement AIbased chatbots and automation tools to enhance customer experience.
  
• Work with big data from property databases and CRM systems to improve decisionmaking.
  
• Deploy and maintain machine learning models using cloud platforms or onpremise solutions.
  
• Collaborate with real estate sales marketing and IT teams to develop AIpowered solutions.
  
• Ensure compliance with data privacy and ethical AI standards.
  

• Bachelors degree in Computer Science Data Science AI/ML or a related field.
  
• Minimum 2 years of experience in AI/ML development with a strong preference for candidates with real estate experience.
  
• Proficiency in Python R or Java and ML frameworks like TensorFlow PyTorch or ScikitLearn.
  
• Experience with data preprocessing feature engineering and model optimization.
  
• Familiarity with real estate CRMs property listing platforms and market trend analysis is a plus.
  
• Experience with cloudbased AI/ML services (AWS Azure Google Cloud).
  
• Strong problemsolving skills and ability to work in a fastpaced environment.
  
• Prior experience developing AI solutions for real estate pricing customer engagement or property analytics.
  
• Knowledge of computer vision for image recognition in real estate listings.
  
• Familiarity with AIdriven marketing automation tools.
  
• Certifications in AI/ML or cloud computing are a plus.
  

Brain Co. is at the leading edge of productionizing artificial intelligence for real world problems, propelling advancements and shaping the future with pioneering work. Our mission is to ensure that the transformative powers and automation of AI are applied to real world problems in various governments where manual work is still dominant. We are seeking visionary AI/ML Engineers with experience in GenAI and ML modeling, where you will convert groundbreaking research into real-world applications that revolutionize industries, boost human creativity, and address complex challenges.

As an AI/ML Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential.

• Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.

• Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.

• Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.

• Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.

• Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices.
  

• Hold a BSc/Master's/PhD degree in Computer Science, Machine Learning, Data Science, or a related field.

• Have experience building GenAI-focused applications with the latest technologies, including but not limited to Agents, reasoning models and RAG.

• Have at least a high level familiarity with the architecture and operation of large language models.

• Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow.

• Possess a strong foundation in data structures, algorithms, and software engineering principles.

• Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges.

• Can work collaboratively with cross-functional teams.

• Thrive in fast-paced environments where priorities or deadlines may compete.

• Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done.

• Competitive salary plus equity

• Daily lunches

• Commuter benefits

• 401(k)

• Medical, Dental and Vision

• Unlimited PTO

This is a hybrid role based out of our Dubai office.

About AI71

AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges.

AI71 builds secure, enterprise-ready applications powered by cutting-edge technology—tailored for knowledge workers and sector-specific needs.

AI71 bridges the gap between advanced AI and real-world impact.

Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.

The Role

Are you an experienced Machine Learning Engineer with a passion for AI? Do you have a proven track record of harnessing the power of data, developing advanced algorithms, and building AI models? If so, AI71 offers a unique opportunity for you to play a pivotal role in shaping AI-driven solutions that have the potential to redefine industries.

As a Machine Learning Engineer at AI71, you'll be responsible for developing, deploying, and optimizing ML / LLM models that power our AI solutions.

You will collaborate with cross-functional teams to translate business challenges into impactful AI products.

What You'll Do

Model Development : Develop, train, and deploy predictive, prescriptive models that enhance the capabilities of our AI solutions.

AI Technologies : Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts.

Cross-Functional Collaboration : Partner with business stakeholders to understand objectives and translate them into actionable machine learning tasks.

Model Optimization : Continuously monitor, evaluate, and improve models based on real-world performance and evolving business needs.

Data Pipeline Maintenance : Implement and manage robust data preprocessing pipelines to ensure high-quality, reliable input data for model development.

What You'll Bring

Experience : 7+ years of experience in AI, Machine Learning, Reinforcement Learning (RL), Data Science, or a related field.

Expertise in LLMs, Agentic AI : Proven experience with Large Language Models (LLMs) and fine-tuning techniques as well as building agentic workflows.

Education : Master's or Ph.D.

in AI, Data Science, Computer Science, Statistics, or a related field.

Programming Proficiency : Strong proficiency in Python

Preference for candidates with a competitive coding background (e.g., ACM / ICPC, NOI / IOI, Top Coder, Kaggle).

Technical Skills : Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), Generative AI technologies, and libraries like Langchain, Weaviate, Langgraph, LlamaIndex, AgenticAI workflows.

Track Record : Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems.

Collaboration : Excellent communication and collaboration skills with the ability to work across interdisciplinary teams.

Why AI71

Mission-Driven Work : Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.

Unparalleled Opportunity : This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.

Career Growth : We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.

World-Class Environment : Enjoy a flexible working environment and the latest tools & technologies needed to do your best work.

We are seeking a highly skilled AI/ML engineer to join our team and contribute to the development of AI-powered solutions.

• The ideal candidate will have hands-on experience in building, deploying, and maintaining machine learning models and GenAI solutions using modern cloud platforms and MLOps practices.
• You will work closely with cross-functional teams to design scalable AI pipelines and integrate LLM-based solutions into production environments.
• Design, implement, and maintain end-to-end ML pipelines using Databricks notebooks, Delta Lake, and MLflow for experiment tracking, model versioning, and lifecycle management.
• Leverage Databricks AutoML for rapid prototyping and efficient model selection in early-stage experimentation.
• Implement ML model deployment workflows using Databricks Jobs and manage serving endpoints with low-latency requirements.
• Design, develop, and deploy ML and GenAI solutions using Python and LLM frameworks.
• Build and deploy ML production systems, contributing to their design and ongoing maintenance.
• Develop and maintain ML pipelines, manage the data lifecycle, and ensure data quality and consistency throughout.
• Assure robust implementation of ML guardrails and manage all aspects of service monitoring.
• Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations.
• Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios.
• Collaborate with cross-functional teams including architects, data engineers, analysts, and business leaders to deliver robust data solutions.
• Write and maintain infrastructure as code using YAML, Implement and manage CI/CD pipelines for ML workflows.
• Ensure model governance and compliance using protocols like Model Context Protocol and A2A Protocol.
• Produce comprehensive documentation including architectural diagrams, data flow maps, runbooks, and lineage tracking artifacts.
• Continuously improve ml pipeline efficiency by identifying performance bottlenecks and reducing compute/storage costs.
• Containerize applications using Docker and manage deployments on Azure.
• Implement DevOps best practices in the data lifecycle, including CI/CD for pipelines, automated testing, and version control.
• Facilitate internal knowledge sharing via technical workshops, peer reviews, and training sessions for continuous team development.

A bachelor's degree in computer science, information technology, or a related field is required; a master's degree is preferred but not mandatory.

Minimum age 21.

A minimum of 3-5 years of hands-on experience in Python software development with a focus on modular, scalable, and efficient coding for AI/LLM-based applications.

Proven track record of building, scaling, and leading complex ML engineering platforms in enterprise environments.

Strong experience designing and deploying cloud-native ML solutions on Azure Databricks, with an emphasis on scalable model training, model management using MLflow, and real-time inference.

Demonstrated success in implementing AI agents or autonomous workflows using tools such as LangGraph, CrewAI, or similar frameworks.

Experience in real-time or near-real-time inference systems and low-latency model serving.

Hands-on experience with Databricks Machine Learning environment, including MLflow tracking, model registry, and production deployment workflows.

Proficient in using Databricks Feature Store, AutoML, and real-time model inference using Databricks Serving or external endpoints.

Familiarity with Databricks Unity Catalog and access control for secure ML asset management.

Advanced proficiency in Python and LLM, with strong skills in performance tuning, modular coding, and automation scripting.

Experience deploying GenAI & related frameworks (e.g., LangChain, LLMOps, PaLM) use cases in Snowflake ecosystem.

Develop, optimize, and maintain scalable machine learning workflows and models using Databricks notebooks and MLflow.

Understanding of how MCPs can complement structured Snowflake data to deliver rich narrative insights, automated clinical summaries, and patient engagement tools.

Build AI-driven applications using Snowflake Cortex, Document AI, and Snowpark ML.

Integrate GenAI tools like OpenAI GPT, Claude (Anthropic), and xAI's Grok to enhance unstructured data processing and generate intelligent summaries or decision recommendations.

Experience in experimentation, feature engineering, Model registration, deployment, and monitoring, using AutoML cost and quota management.

Strong written and verbal communication skills in English, with the ability to influence, mentor, and align technical teams and stakeholders.

Candidates with coursework or academic research in deep learning, reinforcement learning, or natural language processing are highly encouraged.

Databricks Certified Machine Learning Professional

Snowflake SnowPro Core Certification

Azure Data Scientist Associate

This is an office-based position with regular working hours.

At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to innovative infrastructure. In order to deliver on that vision, we've created innovative software and hardware solutions that make it possible.

AWS Neuron is the SDK that optimizes the performance of complex neural net models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads

The Neuron SDK consists of a compiler, run-time, and debugger, integrated with Tensorflow, PyTorch, and MXNet. It's preinstalled in AWS Deep Learning AMIs and Deep Learning Containers for customers to quickly get started with running high performance and cost-effective inference.

The Neuron team is hiring senior compiler engineers in order to solve our customers toughest problems.

This is an opportunity to work on innovative products at the intersection of machine-learning, high-performance computing, and distributed architectures. You will architect and implement business-critical features, publish innovative research, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture.

As a senior deep learning compiler engineer on the Neuron team, you will be a thought leader supporting the development of a compiler targeting AWS Inferentia and Trainum. You will be developing and scaling the compiler to handle the world's largest ML workloads. You will need to be technically capable, credible and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects. A background in machine learning and AI accelerators is preferred, but not required.

Explore the product and our history
the team
#1. Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

#2. Work/Life Balance
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

#3. Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience in compiler design for CPU/GPU/Vector engines/ML-accelerators.
- Experience with System Level performance analysis and optimization
- Experience with LLVM and/or MLIR
- Experience with the following technologies: PyTorch, OpenXLA, StableHLO, JAX, TVM, deep learning models, and algorithms.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.

A strong player in the shipping and logistics industry that are looking to expand their AI and ML capabilities.

• Build and maintain scalable ML pipelines for pricing optimisation, shipping rate prediction, and logistics operations.
• Deploy, monitor, and manage ML models in production using best-practice MLOps frameworks and tools.
• Collaborate with data scientists to take prototypes through to production-grade solutions.
• Implement automated model monitoring, retraining, and version control processes to ensure performance stability.
• Optimise model latency and cost efficiency for real-time decision-making in high-volume transactional environments.
• Partner with engineering teams to streamline data flows from operational systems (ERP, WMS, TMS) and ensure data readiness.
• Champion reproducibility, scalability, and operational excellence in AI delivery.

• Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.
• 4+ years of hands-on experience in MLOps, with a strong background in deploying and managing ML models in production.
• Proven experience in pricing optimisation, shipping, logistics, or supply chain AI solutions.
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with MLOps tools and platforms (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML).
• Solid understanding of CI/CD, containerisation (Docker, Kubernetes), and cloud-based ML infrastructure.
• Experience working with APIs and integrating ML into operational workflows.

A strong player in the shipping and logistics industry that are looking to expand their AI and ML capabilities.

• Build and maintain scalable ML pipelines for pricing optimisation, shipping rate prediction, and logistics operations.
• Deploy, monitor, and manage ML models in production using best-practice MLOps frameworks and tools.
• Collaborate with data scientists to take prototypes through to production-grade solutions.
• Implement automated model monitoring, retraining, and version control processes to ensure performance stability.
• Optimise model latency and cost efficiency for real-time decision-making in high-volume transactional environments.
• Partner with engineering teams to streamline data flows from operational systems (ERP, WMS, TMS) and ensure data readiness.
• Champion reproducibility, scalability, and operational excellence in AI delivery.
• Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.
• 4+ years of hands-on experience in MLOps, with a strong background in deploying and managing ML models in production.
• Proven experience in pricing optimisation, shipping, logistics, or supply chain AI solutions.
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with MLOps tools and platforms (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML).
• Solid understanding of CI/CD, containerisation (Docker, Kubernetes), and cloud-based ML infrastructure.
• Experience working with APIs and integrating ML into operational workflows.
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