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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

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

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

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner. 
Job Description 
Summary
 As the leading delivery platform in the region, we have a unique responsibility and opportunity to positively impact millions of customers, restaurant partners, and riders. To achieve our mission, we must scale and continuously evolve our machine learning capabilities, including cutting-edge Generative AI (genAI) initiatives. This demands robust, efficient, and scalable ML platforms that empower our teams to rapidly develop, deploy, and operate intelligent systems.
As an ML Platform Engineer, your mission is to design, build, and enhance the infrastructure and tooling that accelerates the development, deployment, and monitoring of traditional ML and genAI models at scale. You&rsquo;ll collaborate closely with data scientists, ML engineers, genAI specialists, and product teams to deliver seamless ML workflows&mdash;from experimentation to production serving&mdash;ensuring operational excellence across our ML and genAI systems. 
Qualifications 
Responsibilities<ul><li>
Design, build, and maintain scalable, reusable, and reliable ML platforms and tooling that support the entire ML lifecycle, including data ingestion, model training, evaluation, deployment, and monitoring for both traditional and generative AI models. 
</li><li>Develop standardized ML workflows and templates using MLflow and other platforms, enabling rapid experimentation and deployment cycles. 
</li><li>Implement robust CI/CD pipelines, Docker containerization, model registries, and experiment tracking to support reproducibility, scalability, and governance in ML and genAI. 
</li><li>Collaborate closely with genAI experts to integrate and optimize genAI technologies, including transformers, embeddings, vector databases (e.g., Pinecone, Redis, Weaviate), and real-time retrieval-augmented generation (RAG) systems. 
</li><li>Automate and streamline ML and genAI model training, inference, deployment, and versioning workflows, ensuring consistency, reliability, and adherence to industry best practices. 
</li><li>Ensure reliability, observability, and scalability of production ML and genAI workloads by implementing comprehensive monitoring, alerting, and continuous performance evaluation. 
</li><li>Integrate infrastructure components such as real-time model serving frameworks (e.g., TensorFlow Serving, NVIDIA Triton, Seldon), Kubernetes orchestration, and cloud solutions (AWS/GCP) for robust production environments. 
</li><li>Drive infrastructure optimization for generative AI use-cases, including efficient inference techniques (batching, caching, quantization), fine-tuning, prompt management, and model updates at scale. 
</li><li>Partner with data engineering, product, infrastructure, and genAI teams to align ML platform initiatives with broader company goals, infrastructure strategy, and innovation roadmap. 
</li><li>Contribute actively to internal documentation, onboarding, and training programs, promoting platform adoption and continuous improvement.</li></ul>
Requirements
Technical Experience<ul><li>
Strong software engineering background with experience in building distributed systems or platforms designed for machine learning and AI workloads. 
</li><li>Expert-level proficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch), infrastructure tooling (MLflow, Kubeflow, Ray), and popular APIs (Hugging Face, OpenAI, LangChain). 
</li><li>Experience implementing modern MLOps practices, including model lifecycle management, CI/CD, Docker, Kubernetes, model registries, and infrastructure-as-code tools (Terraform, Helm). 
</li><li>Demonstrated experience working with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed ML services (e.g., Vertex AI, SageMaker). 
</li><li>Proven experience with generative AI technologies: transformers, embeddings, prompt engineering strategies, fine-tuning vs. prompt-tuning, vector databases, and retrieval-augmented generation (RAG) systems. 
</li><li>Experience designing and maintaining real-time inference pipelines, including integrations with feature stores, streaming data platforms (Kafka, Kinesis), and observability platforms. 
</li><li>Familiarity with SQL and data warehouse modeling; capable of managing complex data queries, joins, aggregations, and transformations. 
</li><li>Solid understanding of ML monitoring, including identifying model drift, decay, latency optimization, cost management, and scaling API-based genAI applications efficiently.</li></ul>
Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field; advanced degree is a plus. 
</li><li>2+ years in a tech lead role, 5+ years of experience in ML platform engineering, ML infrastructure, generative AI, or closely related roles.</li><li>
Proven track record of successfully building and operating ML infrastructure at scale, ideally supporting generative AI use-cases and complex inference scenarios. 
</li><li>Strategic mindset with strong problem-solving skills and effective technical decision-making abilities. 
</li><li>Excellent communication and collaboration skills, comfortable working cross-functionally across diverse teams and stakeholders. 
</li><li>Strong sense of ownership, accountability, pragmatism, and proactive bias for action.</li></ul></div>

Staff Engineer - ML Platform

Onliest

Job Title: Machine Learning Engineer &ndash; 3D GraphicsLocation: UAE Experience: 6+ years Job Type: Full-TimeRole: We are seeking a highly skilled and innovative Machine Learning Engineer with 3D Graphics expertise. In this role, you will be responsible for developing and optimizing 3D mannequin models using machine learning algorithms, computer vision techniques, and 3D rendering tools. You will collaborate with backend developers, data scientists, and UI/UX designers to create realistic, scalable, and interactive 3D visualization modules that enhance the user experience.Key Responsibilities:3D Mannequin Model Development:<ul><li>Design and develop 3D mannequin models using ML-based body shape estimation.</li><li>Implement pose estimation, texture mapping, and deformation models.</li><li>Use ML algorithms to adjust measurements for accurate sizing and fit.</li></ul>Machine Learning &amp; Computer Vision:<ul><li>Develop and fine-tune ML models for body shape recognition, segmentation, and fitting.</li><li>Implement pose detection algorithms using TensorFlow, PyTorch, or OpenCV.</li><li>Use GANs or CNNs for realistic 3D texture generation.</li></ul>3D Graphics &amp; Visualization:<ul><li>Create interactive 3D rendering pipelines using Three.js, Babylon.js, or Unity.</li><li>Optimize mesh processing, lighting, and shading for real-time rendering.</li><li>Use GPU-accelerated techniques for rendering efficiency.</li></ul>Model Optimization &amp; Performance:<ul><li>Optimize inference pipelines for faster real-time rendering.</li><li>Implement multi-threading and parallel processing for high performance.</li><li>Utilize cloud infrastructure (AWS/GCP) for distributed model training and inference.</li></ul>Collaboration &amp; Documentation:<ul><li>Collaborate with UI/UX designers for seamless integration of 3D models into web and mobile apps.</li><li>Maintain detailed documentation for model architecture, training processes, and rendering techniques.</li></ul>Key Skills &amp; Qualifications:Experience:<ul><li>3&ndash;8 years in Machine Learning, Computer Vision, and 3D Graphics Development.</li></ul>Technical Skills:<ul><li>Proficiency in Django, Python, TensorFlow, PyTorch, and OpenCV.</li><li>Strong expertise in 3D rendering frameworks: Three.js, Babylon.js, or Unity.</li><li>Experience with 3D model formats (GLTF, OBJ, FBX).</li><li>Familiarity with Mesh Recovery, PyMAF, and SMPL models.</li></ul>ML &amp; Data Skills:<ul><li>Hands-on experience with GANs, CNNs, and RNNs for texture and pattern generation.</li><li>Experience with 3D pose estimation and body measurement algorithms.</li></ul>Cloud &amp; Infrastructure:<ul><li>Experience with AWS (SageMaker, Lambda) or GCP (Vertex AI, Cloud Run).</li><li>Knowledge of Docker and Kubernetes for model deployment.</li></ul>Graphics &amp; Visualization:<ul><li>Knowledge of 3D rendering engines with shader programming.</li><li>Experience in optimization techniques for rendering large 3D models.</li></ul>Soft Skills:<ul><li>Strong problem-solving skills and attention to detail.</li><li>Excellent collaboration and communication skills.</li></ul>Interested candidates can send their updated resume to: careers@onliestworld.comJob Type: Full-time

ML Engineer -3D Graphic

ClearVUE.Business

<div>
 
 
 Hi, we're ClearVUE Dubai
 
 
 
 
 
 
 ClearVUE Dubai is an environmental and energy consultancy and technology provider. We work with companies across all sectors to define and execute their carbon reduction and energy efficiency strategies on their wider ESG initiatives.
 
 
 
 
 
 Through comprehensive energy and carbon assessments and strategy building and implementation services, underpinned by industry-leading energy and carbon management technology, we are creating revolutionary solutions for businesses to eradicate their impact on the climate one step at a time.
 
 
 
 
 
 ClearVUE Dubai is part of Global Procurement Group, a multinational group of companies working in energy procurement and consultancy. Join our global family, with modern and vibrant offices in the UK, France, Malta, and India. Be part of a team leading the way in energy consultancy and helping businesses make informed decisions about their energy consumption.
 
 
 
 
 
 
 The opportunity
 
 
 
 
 
 
 Are you an AI engineer with a passion for data, innovation, and driving real-world impact? We&rsquo;re looking for a skilled and motivated AI Engineer to join our data team in Dubai. In this role, you&rsquo;ll work on impactful projects in energy and sustainability, applying advanced machine learning techniques, AI tools, and large language models (LLMs) to solve complex, real-world challenges and help shape the future of intelligent solutions.
 
 
 
 
 
 
 What exactly will you do?
 
 
 
 
 
 <ul>
 <li>
 Collaborate with our team to analyse and interpret data from diverse sources, including sensors, APIs, and customer platforms.
 </li>
 <li>
 Design, develop, and deploy machine learning models that predict trends, improve efficiency, and generate actionable insights from energy-related data.
 </li>
 <li>
 Build and integrate AI/ML solutions into production environments, ensuring scalability and reliability in real-world applications.
 </li>
 <li>
 Work with modern AI tools such as
 
 OpenAI, Hugging Face, and LangChain
 
 , applying
 
 Retrieval-Augmented Generation (RAG)
 
 and
 
 Model Context Protocol (MCP)
 
 techniques to enhance data relevance, context awareness, and explainability in AI-driven products.
 </li>
 <li>
 Stay current with the latest advancements in AI, data science, and MLOps tools, and bring innovative ideas to the team.
 </li>
 <li>
 Participate in brainstorming sessions, code reviews, and planning meetings; your technical perspective and creativity will help shape our solutions.
 </li>
 <li>
 Contribute to dashboards, reports, and prototypes that translate complex data into clear, actionable insights for clients and internal teams.
 </li>
 </ul>
 
 
 
 
 
 What we&rsquo;re looking for
 
 
 
 
 
 <ul>
 <li>
 3 &ndash; 5 years of experience working as an
 
 AI Engineer
 
 or similar role.
 </li>
 <li>
 Bachelor&rsquo;s Degree in
 
 Computer Science, Data Science, Engineering, Maths, Physics
 
 , or a related field.
 </li>
 <li>
 Hands-on experience with
 
 Python
 
 ,
 
 data analysis
 
 , or
 
 machine learning
 
 .
 </li>
 <li>
 Solid understanding of AI/ML concepts (e.g., building and evaluating models, using Jupyter notebooks, working with LLM APIs).
 </li>
 <li>
 Proficiency in data manipulation using tools such as
 
 pandas
 
 ,
 
 NumPy
 
 , and
 
 SQL
 
 .
 </li>
 <li>
 Experience with
 
 scikit-learn
 
 ,
 
 TensorFlow
 
 , or
 
 PyTorch
 
 , and familiarity with LLM frameworks such as
 
 OpenAI API
 
 or
 
 LangChain
 
 .
 </li>
 <li>
 Excellent communication skills; you can clearly explain technical concepts to both technical and non-technical audiences
 </li>
 <li>
 A proactive team player with a growth mindset, eager to learn, share knowledge, and contribute to meaningful projects
 </li>
 </ul>
 
 
 
 
 
 Nice to Have (but not expected)
 
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s Degree in related field.
 </li>
 <li>
 Experience implementing
 
 RAG pipelines
 
 or
 
 MCP-based integrations
 
 to connect AI models with live enterprise data sources.
 </li>
 <li>
 Knowledge of time series data or experience working with energy, IoT, or sustainability projects.
 </li>
 <li>
 Familiarity with cloud platforms (AWS, GCP, or Azure) or tools like Git, Docker, or APIs.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us?
 
 
 
 
 
 
 This is your chance to work with a team building technology that actually matters, not just another app, but a platform helping organisations become more energy efficient and sustainable. We&rsquo;ll support your growth, celebrate your ideas, and push the boundaries of what software can do in today&rsquo;s energy landscape.
 
 
 
 
 
 
 What&rsquo;s in it for you?
 
 
 
 
 
 
 💎
 
 Compensation Package:
 
 We offer a
 
 monthly base salary of 16,000 AED
 
 , plus
 
 comprehensive medical insurance.
 
 
 
 🌍
 
 Purpose-Driven Impact:
 
 Play a vital role in fighting climate change. Your work will directly contribute to reducing global carbon emissions and improving sustainability for businesses worldwide.
 
 
 🚀
 
 Ongoing Support and Development:
 
 Receive ongoing training, mentorship, and guidance from industry experts to help you build skills and develop professionally every step of the way.
 
 
 📈
 
 Clear Path to Advancement:
 
 We believe in nurturing our own; promotions from within are our specialty.
 
 
 
 
 
 
 GPG is an equal opportunity employer and applicants will be considered for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
 
 
</div>

AI Engineer

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3794 machine learning platform engineer jobs IN Dubai

ML Platform Engineer

ML Platform Engineer

ML Platform Engineer Generative AI & Machine Learning Infrastructure

ML Platform Engineer Generative AI & Machine Learning

Staff Engineer - ML Platform

ML Engineer -3D Graphic

AI Engineer