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Thales

JOB OBJECTIVE We are seeking a talented and enthusiastic AI/ML professional to join our team. This position is ideal for recent graduates or final year students in Computer Science or IT Engineering who are passionate about machine learning and artificial intelligence. The incumbent will play a key role in helping us define a solution to digitalize documents and develop a system capable of predicting qualifications based on database analysis. ROLES &amp; RESPONSIBILITIES <ul> <li>Collaborate with senior officials to understand project requirements and goals.</li> <li>Assist in the development and implementation of a machine-learning model to process and digitalize various documents.</li> <li>Work on algorithms that analyze data from the digital documents to make predictions about qualifications.</li> <li>Perform data preprocessing and cleaning to ensure high-quality input for the machine learning models.</li> <li>Conduct experiments and evaluations to measure the effectiveness of different models and approaches.</li> <li>Document processes, methodologies, and findings for future reference and knowledge sharing.</li> <li>Present progress updates and findings to the team in a clear and concise manner.</li> </ul> WORK EXPERIENCE REQUIREMENTS <ul> <li>Solid understanding of machine learning concepts and algorithms.</li> <li>Experience with programming languages such as Python, R, or Java.</li> <li>Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.</li> <li>Knowledge of data preprocessing techniques and tools.</li> <li>Strong analytical and problem-solving skills.</li> <li>Excellent communication and teamwork abilities.</li> <li>Ability to learn quickly and adapt to new challenges.</li> </ul> QUALIFICATION, CERTIFICATION &amp; EDUCATIONAL REQUIREMENTS <ul> <li>Educational background in Computer Science, IT Engineering, or a related field.</li> </ul> PREFERRED SKILLS <ul> <li>Experience with natural language processing (NLP) and document digitalization.</li> <li>Understanding of database design and management.</li> <li>Familiarity with cloud services and deployment (AWS, Azure, GCP).</li> <li>Previous internship or project experience in AI/ML.</li> </ul> HSE RESPONSIBILITIES* <ul> <li>Ensure both your own safety and the safety of others at all times.</li> <li>Maintain an active role in achieving the objectives and adhering to the HSE Thales Policy</li> <li>Comply with local HSE laws and legislation.</li> <li>To use safety equipment (including PPE) as required and intended.</li> <li>Lead by example and actively encourage departments to look at ways to conserve water &amp; energy, minimise the generation of waste, and encourage recycling.</li> <li>Every one within Thales has the right to stop work if they believe that their activities may affect their health and safety or that of others. In this circumstance, such conditions must be reported immediately to their line manager and the HSE department.</li> </ul>

Graduate AI/ML Engineer

Glow Beauty On Demand

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer Generative AI & Machine Learning Infrastructure

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies What We Offer * Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East * Competitive salary and benefits package * A collaborative, innovation-driven environment with cutting-edge tools and technologies * Career development in one of the fastest-growing tech ecosystems in the region

ML Platform Engineer Generative AI & Machine Learning

B&B Hotel Hannover-City

Are you passionate about combining machine learning and physics to accelerate simulation and optimization in energy systems? This is an exciting opportunity to join one of our major global clients as a Machine Learning Engineer &ndash; Physics-Based Surrogate Modelling, where you will design and deploy Graph Neural Network (GNN) and physics-informed neural network (PINN) models to emulate complex physical simulations for pipeline and well network systems.The role focuses on developing scalable surrogate models that capture multi-physics flow dynamics, reduce simulation costs, and enhance production optimization workflows. You will work at the intersection of data science, physics, and software engineering, transforming simulation data into actionable machine learning frameworks for predictive performance and real-time decision support.Key Responsibilities<ul><li>Develop, train, and deploy Graph Neural Network (GNN)-based surrogate models to approximate physics-based simulations for pipeline and well networks.</li><li>Design data transformation pipelines to convert numerical simulation outputs into graph representations suitable for deep learning architectures.</li><li>Integrate physics constraints and governing equations into neural network loss functions to ensure physically consistent predictions.</li><li>Implement Physics-Informed Neural Networks (PINNs) and hybrid ML-physics models for flow dynamics and pressure prediction.</li><li>Collaborate with domain experts to interpret simulation data, validate model outputs, and ensure consistency with reservoir and production physics.</li><li>Optimize model training for scalability, accuracy, and generalization across varying simulation conditions.</li><li>Build and automate model evaluation, versioning, and deployment frameworks using MLOps tools.</li><li>Develop visualization and post-processing tools to analyze surrogate model behavior and compare results with high-fidelity simulators.</li><li>Document methodologies, validation reports, and research findings for knowledge transfer and technical review.</li><li>Stay current with emerging trends in scientific machine learning, GNNs, and physics-informed AI frameworks.</li></ul>Required Qualifications / Experience / Skills<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Applied Mathematics, Petroleum Engineering, Mechanical Engineering, or a related field (Ph.D. preferred).</li><li>Minimum 7+ years of experience in machine learning model development, with focus on physics-based or scientific ML applications.</li><li>Proven expertise in Graph Neural Networks (GNNs) using frameworks such as PyTorch Geometric, DGL, or DeepMind Graph Nets.</li><li>Experience developing Physics-Informed Neural Networks (PINNs) or hybrid ML models incorporating domain constraints.</li><li>Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).</li><li>Solid understanding of numerical simulation, PDEs, and fluid dynamics in pipeline or reservoir systems.</li><li>Familiarity with data preprocessing, feature engineering, and large-scale scientific data handling.</li><li>Hands-on experience with MLOps tools (MLflow, Docker, Git, CI/CD pipelines) for model deployment and version control.</li><li>Ability to work cross-functionally with simulation engineers, data scientists, and domain specialists.</li><li>Strong analytical, mathematical modeling, and problem-solving skills with attention to detail.</li><li>Excellent written and verbal communication skills for technical documentation and presentations.</li></ul>Job Location 100% Remote / HybridType of Employment Full-time / PermanentSalary: NegotiableWhat You Can Expect from the Employer<ul><li>Opportunity to work with a global leader in energy and simulation technology.</li><li>Exposure to cutting-edge AI research and scientific computing.</li><li>Competitive compensation and benefits package.</li><li>Collaborative and innovation-driven environment with professional growth opportunities.</li></ul>Job Types: Full-time, PermanentApplication Question(s):<ul><li>Do you have 7 or more years of experience developing deep learning or physics-based ML models?</li><li>Have you built or deployed Graph Neural Network (GNN) or Physics-Informed Neural Network (PINN) models in production or research settings?</li><li>Are you proficient in Python and experienced with frameworks such as PyTorch Geometric or DGL for physics-based modeling?</li></ul>

Machine Learning Engineer – Physics-Based Surrogate Modelling

DICETEK LLC

<div>Experience Required (Number of Years): 10-15 Years
Description :
Skill/Experience/Qualification
Analyze large datasets to identify trends, patterns, and actionable insights.
Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.
Collaborate with stakeholders to define business problems and translate them into data science solutions.
Communicate findings through visualizations, dashboards, and presentations.
Stay up to date with the latest data science techniques and tools.
Experience with cloud platforms (AWS, Azure)
Familiarity with big data technologies (Spark, Hadoop).
Knowledge of MLOps and model deployment best practices.
Strong understanding of statistical methods and data modeling.</div>

Machine Learning OPS and Data Science

Luxoft

Work directly with computer vision perception engineers, and camera ISP engineers.
Define the image quality requirements for customer use cases
Develop image processing algorithms to optimizing the camera image quality for performance improvement of computer vision applications
Develop custom ML models for visual recognition and training it from scratch
Quantization and pruning the ML models
Data evaluation using relevant metrics to increase the model performance
Implement computer vision/image processing algorithms in fast/optimal C++ code
Implement heuristic/math algorithms and probabilistic methods for camera AI
Research existing C++ solutions for CV logic
Develop cross platform C++ code
Cover algorithms and CV code with unitest
Ramp up on new technologies related to CV/ML/algorithms (not R&amp;D)
Integrate machine learning modules into algorithms

Lead Machine Learning, Computer Vision Software Engineer

GE Aerospace

<div><h1 class="jobSectionHeader">Job Description Summary</h1>
Company Overview: 
 
Working at GE Aerospace means you are bringing your unique perspective, innovative spirit, drive, and curiosity to a collaborative and diverse team working to advance aerospace for future generations. If you have ideas, we will listen. Join us and see your ideas take flight!<h1 class="jobSectionHeader">
Job Description</h1><div><div>
Site Overview:</div></div><div><div><div><div><div><div><div><div><div>
For over 40 years, GE Aerospace has had a significant presence on the ground in the United Arab Emirates. With offices in Abu Dhabi and Dubai Airport Freezone; an On Wing Support Center; partnership engineering, testing, and Maintenance, Repair, and Overhaul facilities across the country; and the Middle East Technology Center focused on solutions for the region&rsquo;s hot &amp; harsh environment. In addition to career opportunities, our sites offer a culture focused on respect for people and giving back to the community through grants and philanthropic programming.
Role Overview:
Are you ready to see your future take flight? At GE Aerospace, we believe the world works better when it flies. We are a world-leading provider of jet engines, components, and integrated systems for commercial and military aircraft. We have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen.
At GE Aerospace Technology &amp; Operations, our customers challenge us to tackle some of the world&rsquo;s most complex engineering problems that require innovative approach using new technologies. Our engineers depend on software developers to bridge data, tools, and emerging technologies, like cloud and AI, to unlock new possibilities and shape the future of flight.
What You will Do<ul><li>
Develop technical solutions for engineers to evaluate and adopt data and AI solutions.</li><li>
Consult on architecture, implement proof of concepts and deliver solutions for business strategic projects, including data science and machine learning systems</li><li>
Build and present product architectures, write technical code, and demo applications to stakeholders.</li><li>
Gain hands-on experience with the Innovator Method and turn customer insights into solution that deliver real business value</li><li>
Sharpen your skills in cloud platforms, databases, data engineering, web design, AI technologies, and numerical methods</li><li>
Use your strengths to support team members and build cross-functional relationships across the company.</li><li>
Work to ship solutions to production that meet business needs and drive impact.</li></ul>
Our culture thrives on innovation, diversity, and deep collaboration. You&rsquo;ll contribute as both a learner and a builder, helping us push the design frontier in aerospace.
Required Qualifications:<ul><li>
Graduate or pursuing a bachelor&rsquo;s degree in computer science, Aerospace Engineering, Mechanical Engineering or a related field at an accredited university or credentialed software accelerator program.</li><li>
Minimum 3.7 cumulative GPA off a 4.0 scale without rounding</li></ul><ul><li>
Strong academic performance in Computer Science or other STEM disciplines</li><li>
Experience designing AI solutions and architecting distributed data systems</li><li>
 Proficiency in programming and debugging with Python, C#, C++, and SQL</li><li>
Customer-centric mindset with ability to lead design thinking workshops</li><li>
Hands-on experience in at least one of the following areas: Machine Learning, Large Language Models (LLMs), or Computer Vision</li><li>
Experience building solutions using public cloud platforms such as AWS or Azure</li><li>
Preferred but not required: AWS and/or Azure certification</li><li>
No prior work experience required</li></ul>
About The Internship<ul><li>
Time: Winter (Full-time) and Spring (Part-time)</li><li>
Location: Remote</li><li>
Paid Internship</li><li>
Travel Opportunities</li><li>
Real-world project ownership</li><li>
Mentorship from experienced engineers</li><li>
Opportunity for return offers</li></ul>
At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.</div></div></div></div></div></div></div></div></div><h1 class="jobSectionHeader">
Additional Information</h1><div><div><div><div><div><div><div>
Relocation Assistance Provided: No</div></div></div></div></div></div></div>
#LI-Remote - This is a remote position</div>

Artificial Intelligence Intern

Explore 1498+ Machine learning intern in Dubai this November. Find roles across top companies and apply now to boost your career.