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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

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

Client of Talent Bridge HR Consultancy Dubai

Role Summary 
Design, build, and fine-tune AI systems that power real healthcare impact. Success looks like shipping reliable models to production, improving accuracy/latency/cost, and running reproducible experiments. This role sits within the core AI team and partners with product, data, and engineering to turn research into scalable products.
 Responsibilities 
<ul>
 <li>Design, train, fine-tune, and evaluate models (LLMs, embeddings) for production use cases.</li>
 <li>Build reproducible data/ETL pipelines and experiment tracking.</li>
 <li>Implement MLOps best practices (versioning, CI/CD for models, monitoring, rollback).</li>
 <li>Run benchmarking, A/B tests, error analysis; document findings and decisions.</li>
 <li>Create internal tools/SDKs for inference, evaluation, and prompt engineering.</li>
 <li>Deploy via REST APIs and optimize for performance and cost.</li>
 <li>Communicate results to technical and non-technical stakeholders.</li>
</ul>
 Qualifications 
<ul>
 <li> Skills: Python (essential); TensorFlow/PyTorch; Hugging Face; Pandas/NumPy/Scikit-learn; ETL; visualization (Matplotlib/Plotly/Tableau/Power BI); NLP &amp; GenAI (LLM fine-tuning, embeddings, prompt engineering); statistics (hypothesis testing, regression).</li>
 <li> Nice to have: C++/Java; publications or patents; Unreal Engine exposure.</li>
 <li> Environment: Solid Linux background for development and deployment.</li>
 <li> Education/Experience: Relevant degree or equivalent practical experience.</li>
</ul>

AI/ML Engineer |Core AI Developer

Location: Dubai, United Arab EmiratesIn fast changing markets, customers worldwide rely on Thales. Thales is a business where brilliant people from all over the world come together to share ideas and inspire each other. In aerospace, transportation, defence, security and space, our architects design innovative solutions that make our tomorrow's possible.Thales has built a presence in the United Arab Emirates for over 35 years, and today has over 300 employees. Thales in the UAE is part of our Middle East business that has 1,800 people across Egypt, Iraq, Kuwait, KSA, Lebanon, Oman, Pakistan, Qatar and UAE. Together we delivered technology for the Dubai metro, the longest driverless metro network in the world and a fare collection system that processes up to 250,000 transactions per day. We make UAE a safer place by providing secure electronic payment solutions, cyber security systems and communications as well as security systems for Dubai International Airport and air traffic management and navigation systems for Abu Dhabi s airport.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 Collaborate with senior officials to understand project requirements and goals.Assist in the development and implementation of a machine-learning model to process and digitalize various documents.Work on algorithms that analyze data from the digital documents to make predictions about qualifications.Perform data preprocessing and cleaning to ensure high-quality input for the machine learning models.Conduct experiments and evaluations to measure the effectiveness of different models and approaches.Document processes, methodologies, and findings for future reference and knowledge sharing.Present progress updates and findings to the team in a clear and concise manner.WORK EXPERIENCE REQUIREMENTS Solid understanding of machine learning concepts and algorithms.Experience with programming languages such as Python, R, or Java.Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.Knowledge of data preprocessing techniques and tools.Strong analytical and problem-solving skills.Excellent communication and teamwork abilities.Ability to learn quickly and adapt to new challenges.QUALIFICATION, CERTIFICATION &amp; EDUCATIONAL REQUIREMENTS Educational background in Computer Science, IT Engineering, or a related field.PREFERRED SKILLS Experience with natural language processing (NLP) and document digitalization.Understanding of database design and management.Familiarity with cloud services and deployment (AWS, Azure, GCP).Previous internship or project experience in AI/ML.HSE RESPONSIBILITIES*Ensure both your own safety and the safety of others at all times.Maintain an active role in achieving the objectives and adhering to the HSE Thales PolicyComply with local HSE laws and legislation.To use safety equipment (including PPE) as required and intended.Lead by example and actively encourage departments to look at ways to conserve water &amp; energy, minimise the generation of waste, and encourage recycling.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.At Thales we provide CAREERS and not only jobs. With Thales employing 80,000 employees in 68 countries our mobility policy enables thousands of employees each year to develop their careers at home and abroad, in their existing areas of expertise or by branching out into new fields. Together we believe that embracing flexibility is a smarter way of working. Great journeys start here, apply now!

Graduate AI/ML Engineer - UAE National

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

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

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