1 314 Machine Learning Engineer jobs in the United Arab Emirates

Messilat is seeking a talented MLOps Engineer for our client's team. The perfect candidate will excel in deploying models, managing microservices, utilizing Docker, and maintaining Kubernetes. Our client is also exploring AI applications in customer service, cybersecurity, and compliance.

Key Responsibilities

• Transition models from development to production, ensuring scalability and high performance. Collaborate with development teams for seamless model deployment.
• Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.
• Maintain Kubernetes clusters to ensure high availability and performance.
• Work with cross-functional teams to understand business requirements and deliver effective machine learning solutions.
• Develop and implement strategies that optimize efficiency and data quality.

Qualifications

• Minimum of 3 years of experience in MLOps or a related field.
• Expertise in model deployment, containerization, and orchestration (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (e.g., AWS, or on-premises) for model deployment and management.
• Experience in deploying AI models and managing their lifecycle.
• Proficiency in Python for scripting and automation.
• Prior experience in addressing scalability and pricing concerns in ML operations.

Skills

• Model deployment, monitoring, Docker, Kubernetes, AWS Cloud services, on-premises deployment, collaboration.

If you are passionate about MLOps and looking for a challenging role where you can make a significant impact, we would love to hear from you. Apply today!

Job Title – ML Engineer

Job Overview

This role involves expertise in designing, implementing, and deploying machine learning and neural network models, particularly in the realms of image processing, object character recognition (OCR) and feature extraction. The ideal candidate should have a strong background in image processing and implementing/deployment neural network models.

Key Responsibilities

• Perform feature extraction on images with varying levels of reflection, shadows, contrast and exposure, to maximize the utility of the underlying image.
• Optimize existing models to improve performance and efficiency for real-world applications.
• Create efficient models for image forensics, id classification, face liveness and document verification.
• Aware of the latest developments in deep learning and computer vision and incorporate cutting-edge techniques into our workflows.
• Conduct rigorous testing and validation of models to ensure robustness and reliability. Perform data augmentation to create more validation sets.
• Deploying neural networks across cloud services (such as AWS or GCP) for integration with other applications.
• Establishing a reinforcement learning system to facilitate automatic model retraining at regular intervals.
• Documenting the process and the algorithms designed, following the software development best practices.
• Ability to deep dive into research papers and implement the process for feasibility study for any research-oriented tasks.
• Adept with the concept of transformers and ability to create custom RAGs and LLMs for summary, clustering, translation and classification tasks.

Qualifications

• Bachelor's degree in fields like Computer Science, Engineering, Mathematics, or similar technical disciplines.
• At least 3 years of practical experience in crafting and deploying neural network architectures, including a minimum of one year focused on image processing and feature extraction techniques.
• Proficient understanding of various deep learning platforms, including but not limited to TensorFlow, PyTorch, Keras, emphasizing their application in computer vision and convolutional neural networks.
• Strong proficiency in Python programming, along with a good grasp of software engineering principles.
• Skilled at implementing neural networks on cloud platforms, enabling team members to integrate them into diverse applications as required.
• Quick at learning, agile in development practices and ability to improve the system at every step.

Preferred Skills

• Experience with cloud services such as AWS for model training and deployment.
• Familiarity with MLOps practices and tools to manage the machine learning lifecycle.

Job Type: Full-time

Experience:

• Python: 3 years (Required)
• Natural Language Processing: 1 year (Required)
• Image Processing: 1 year (Required)
• Neural Networks: 1 year (Required)

Machine Learning Engineer

Based in Dubai

Please note - the opportunity is only open to those who already reside in Dubai

Salary on offer is between Dh18,000-22,000 p/m

Searchability MENA are partnered with cutting edge tech innovator, specializing in AI and immersive technologies, delivering next-generation solutions that redefine how people interact, create, and communicate in digital environments.

They are looking for an innovative
ML Engineer
to innovate at the intersection of AI, computer vision, and facial reenactment.

This is a rare opportunity that you don't want to miss out on, joining a business that's paving the way for AI-driven holographic experiences.

Here's what they're looking for:

Machine Learning
(ML) model development and deployment.

MLOps
pipelines and workflow automation.

PyTorch
and other ML frameworks.

Computer Vision
and
NLP
applications.

Exposure to end-to-end experience in building, scaling, and maintaining AI/ML systems

Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field—or equivalent experience.

The benefits:

Full Visa Sponsorship and Medical Insurance.

Does this sound exactly what you're looking for?

Hit apply today and we can discuss further

**Please note - that only suitable candidates will be contacted for this position**

Position: Lead AIML Engineer– 3D Mannequin & Virtual Fitting Room

Experience: 6+ years

Location: UAE(Dubai)

Company: Onliest LLC

Website:

About the Company:

Onliest is a fast-growing fashion-tech startup headquartered in the USA with strategic presence in Dubai's DMCC AI Innovation Hub, India, and upcoming production facilities in Sharjah and India. We are on a mission to become the world's only and most exclusive premium brand—where fashion meets artificial intelligence and immersive technology.

Our platform redefines how people experience clothing through personalized 3D design, AR-based virtual try-ons, and AI-powered avatars.

Your Role

We're hiring a
lead, full-stack AIML Engineer
 to independently
build and deliver a complete 3D mannequin system
 powered by AI and computer vision.

You will lead the end-to-end development of an intelligent virtual fitting solution that takes user video as input, reconstructs accurate body mannequins (including full measurements and circumferences), applies designed garments, and presents them in different poses and scenes — with seamless integration into AR platforms.

What You'll Own

· 3D Avatar Reconstruction from Video

o Use computer vision to analyze user-submitted video and generate a realistic, scalable 3D mannequin

o Extract full body measurements (height, waist, bust, hips, arms, legs, etc.) and body ratios

o Handle diverse body types, poses, and camera angles with high precision

· Dress Simulation & Virtual Fitting

o Overlay user-customized digital outfits onto the mannequin in a real-time virtual fitting environment

o Simulate clothing physics, fabric behavior, and natural body movement

o Render the dressed mannequin in multiple poses and animations

· AI/ML Pipeline Development

o Develop and train models for pose estimation, segmentation, measurement prediction, and 3D mesh generation

o Optimize for both speed and accuracy using lightweight, scalable ML models

o Automate personalization using inferred features like gender, fit preferences, and style

· AR Integration

o Enable viewing of the dressed mannequin in real-world spaces using ARKit, ARCore, or WebAR

o Work with frontend team (or use existing WebAR solutions) to integrate AR visualizations

· Deployment & Ownership

o Build robust backend in Python (FastAPI/Flask) for mannequin generation services

o Maintain model performance, data pipelines, and API readiness for integration into our fashion platform

o Own testing, optimization, documentation, and user input quality management

Who You Are

· 5+ years of experience in Python development with a focus on AI/ML and computer vision

· Proven experience building
3D avatar or mannequin generation systems
 from 2D data or videos

· Deep knowledge of
pose estimation, segmentation, photogrammetry, and 3D mesh reconstruction

· Experience with tools like
MediaPipe, OpenPose, OpenCV, PyTorch, TensorFlow, or Detectron2

· Familiarity with
3D engines or rendering frameworks
 like Blender (Python scripting), Unity, or

· Exposure to
AR technologies
 like ARKit, ARCore, or WebXR

· Strong understanding of garment simulation, virtual fitting, or clothing try-on techniques

· Ability to work independently, manage deliverables end-to-end, and collaborate with product/design remotely

· Experience integrating with or Unity3D

Nice-to-Have

· Background in fashion tech or body scanning applications

· Passion for personalized fashion experiences and human-centric AI

· Prior work in real-time avatar animation, retargeting, or NeRFs (bonus)

Interested can share their resume to

JOB DESCRIPTION SUMMARY

The Machine Learning Engineer role will specialise in maintaining scoring models, production system maintenance and high-availability operations. You'll orchestrate and maintain our AzureML/Databricks-based scoring engine, ensure 99.99% uptime for production models, perform emergency fixes, and manage QA/UAT processes. This role partners with data scientists to operationalize models and data engineers to ensure efficient data flows.

KEY DUTIES & RESPONSIBILITIES

• Production Model Maintenance:
  Monitor, troubleshoot, and rectify issues in deployed credit scoring models (e.g., score drift, feature misalignment, output anomalies).
• Platform Orchestration:
  Manage AzureML pipelines & Databricks workflows for model retraining, batch scoring, and real-time inference.
• High-Availability Engineering:
  Ensure 24/7 uptime of scoring APIs serving banking clients; implement failover systems and load balancing.
• Release Management:
  Oversee QA/UAT processes for model updates including back-testing, shadow deployments, and canary releases.
• Model Governance:
  Maintain audit trails for model versions, inputs/outputs, and performance metrics. Support Compliance and Audit with creation of logs when requested.
• Incident Response:
  Lead troubleshooting of scoring engine failures with SLAs for financial institution clients.
• Infrastructure Optimization:
  Tune AzureML/Databricks clusters for cost-performance efficiency at scale.
• Vendor Management:
  Ensure vendor support is completing work as per scope and SLAs. Rectifying any vendor delivery issues.

EDUCATION & SKILLS

1. Educated with at least bachelor's degree or equivalent in related field
2. Education specialization or master's degree in computer science, Software Engineering
3. Proficient in English
4. Preferred proficiency in Arabic
5. In-depth knowledge of React Native and Next JS and related modules, components and libraries
6. Preferred In-depth knowledge of SiteCore or experience integrating with SiteCore

EXPERIENCE & KNOWLEDGE

1. Bachelor's/Master's in Computer Science, Engineering, Data Science, or related field
2. 2+ years in Data Science or Software Engineering experience
3. 2+ years production ML operations experience, MLOps lifecycle management, including monitoring, retraining, and model versioning.
4. Strong problem-solving skills and the ability to resolve issues efficiently.
5. CI/CD for ML systems using tools such as Azure DevOps, GitHub Actions, MLflow, and other similar tools
6. Ability to adapt ML workflows across different cloud environments (Azure, AWS, GCP) as needed.

ABILITIES & SPECIFIC REQUIREMENTS

1. Practical experience in cloud-based ML platforms such as AzureML, Databricks, or equivalent (e.g., SageMaker, Vertex AI), with a preference for Azure.
2. Python/PySpark for model debugging and patching. Working knowledge of Scikit-Learn and NumPy
3. Deep understanding of credit scoring systems: feature engineering, scorecard interpretation, and output validation
4. Credit bureau data structures (tradelines, inquiries, public records)
5. Model risk management (MRM) standards
6. Azure Solutions Architect or MLOps certifications
7. Experience with financial services-grade SLAs (99.9% uptime) and outage management
8. Knowledge of containerization (Docker, Kubernetes, AKS, or similar orchestration tools)
9. Practical experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) / Azure Blob Storage
10. Knowledge of new and upcoming AI tools
11. This is contained within the earlier requirement of python. If the plan is for this resource
12. Excellent written and verbal communication skills English
13. Strong interpersonal skills with the ability to engage and build relationships
14. Crisis management under pressure
15. Cross-functional collaboration with data science/risk teams
16. Strong organizational skills with the ability to manage multiple tasks and projects simultaneously.
17. Ability to develop and document procedures, roles, and guidelines.
18. Security and Compliance
    Especially in financial services, mention data security, PII handling, and compliance with regulations

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

We are seeking AI/ML Engineer with expertise in computer vision and image processing. The ideal candidate will develop and optimize deep learning models / VLMs for object detection, segmentation, classification, text extraction, and fine-tuning for domain-specific applications.

What You'll Do:

Develop & Deploy AI Models:

• Train and optimize object detection, segmentation, and classification models for architectural drawings.
• Fine-tune YOLO, R-CNN, and Transformer-based models to improve accuracy and efficiency for domain-specific tasks.
• Implement OCR and symbol recognition for automated compliance checking.

Image Processing & Enhancement:

• Develop lossless image compression and feature extraction techniques.
• Improve image pre-processing pipelines for architectural data quality.
• Utilize OpenCV and Deep Learning for drawing analysis.

Fine-Tuning & Model Adaptation:

• Customize and fine-tune pre-trained vision-language models (VLMs) while enabling their multimodal AI capabilities.
• Optimize model parameters, embeddings, and transfer learning strategies to enhance performance and efficiency.
• Continuously improve AI models based on real-world feedback, evolving datasets, and domain requirements.

AI Model Optimization & Deployment

• Optimize model architectures to reduce computational costs while maintaining accuracy.
• Deploy AI models on cloud or on-prem infrastructure with Docker/Kubernetes is a plus.
• Integrate AI workflows into AutoCAD and BIM environments is a plus.

What You'll Bring:

• Computer Vision & Deep Learning: OpenCV, YOLO, R-CNN, Mask R-CNN, EfficientNet
• OCR & Symbol Extraction: Tesseract, EasyOCR, NLP for document parsing
• Fine-Tuning & Transfer Learning: Vision-Language Models (VLMs), CLIP, Transformer-based architectures
• Programming: Python, C++
• Cloud & Deployment: AWS, Azure, GCP, TensorFlow Serving, ONNX
• Image Processing: Feature extraction, noise reduction, compression techniques
• 7+ years of Experience in the computer vision solutions
• Strong problem-solving skills in computer vision applications.
• Ability to optimize AI pipelines for real-world datasets.
• Experience integrating AI models into software applications.
• Familiarity with CAD tools (AutoCAD, Revit, DXF/DWF processing) is a plus.

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.

Title: ML Engineer - 3D Graphic Specialist

Location:
UAE/Visakhapatnam

Experience:
6+ Years

Type:
Full-time

Role:

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:

• Design and develop 3D mannequin models using ML-based body shape estimation.

• Implement pose estimation, texture mapping, and deformation models.

• Use ML algorithms to adjust measurements for accurate sizing and fit.

Machine Learning & Computer Vision:

• Develop and fine-tune ML models for body shape recognition, segmentation, and fitting.

• Implement pose detection algorithms using TensorFlow, PyTorch, or OpenCV.

• Use GANs or CNNs for realistic 3D texture generation.

3D Graphics & Visualization:

• Create interactive 3D rendering pipelines using , , or Unity.

• Optimize mesh processing, lighting, and shading for real-time rendering.

• Use GPU-accelerated techniques for rendering efficiency.

Model Optimization & Performance:

• Optimize inference pipelines for faster real-time rendering.

• Implement multi-threading and parallel processing for high performance.

• Utilize cloud infrastructure (AWS/GCP) for distributed model training and inference.

Collaboration & Documentation:

• Collaborate with UI/UX designers for seamless integration of 3D models into the web and mobile apps.

• Maintain detailed documentation for model architecture, training processes, and rendering techniques.

Key Skills & Qualification:

Experience:
6+ years in Machine Learning, Computer Vision, and 3D Graphics Development.

Technical Skills:

• Proficiency in Django, Python, TensorFlow, PyTorch, and OpenCV.

• Strong expertise in 3D rendering frameworks: , , or Unity.

• Experience with 3D model formats (GLTF, OBJ, FBX).

• Familiarity with Mesh Recovery, PyMAF, and SMPL models.

ML & Data Skills:

• Hands-on experience with GANs, CNNs, and RNNs for texture and pattern generation.

• Experience with 3D pose estimation and body measurement algorithms.

Cloud & Infrastructure:

• Experience with AWS (SageMaker, Lambda) or GCP (Vertex AI, Cloud Run).

• Knowledge of Docker and Kubernetes for model deployment.

Graphics & Visualization:

• Knowledge of 3D rendering engines with shader programming.

• Experience in optimization techniques for rendering large 3D models.

Soft Skills:

• Strong problem-solving skills and attention to detail.

• Excellent collaboration and communication skills.

To Apply:
Send your resume to

Machine Learning Engineer (classification, detection, clustering, time-series)

Our client is developing a next-generation distributed infrastructure that turns idle digital resources into real-time, high-throughput data streams for AI and large-scale analytics. Supported by leading investors and seasoned founders, the company has gained significant traction with a large user base, maintains a high-performance, ownership-driven culture, and operates across multiple international hubs. They are assembling a team of exceptional professionals to drive their next phase of growth.

Role Requirement

We're searching for a skilled
Machine Learning Engineer
to help our client scale their next-generation multimodal data infrastructure. This hands-on role combines system-level design with technical execution, ensuring pipelines that process audio, video, text, and image data are robust, scalable, and production-ready. The Machine Learning Engineer will work closely with internal teams and external stakeholders to transform complex data into actionable intelligence, while leading end-to-end ML projects from initial design through deployment, delivering high-impact solutions across diverse B2B use cases.

Responsibilities

• Develop, train, and fine-tune classical machine learning models across diverse multimodal datasets, including audio, video, text, and images.
• Build and maintain reliable pipelines for model evaluation, testing, and performance monitoring.
• Develop and operate scalable ETL/ETN workflows to continuously ingest, process, and clean datasets at petabyte scale.
• Uphold data integrity, reproducibility, and regulatory compliance, including GDPR and CCPA standards.
• Support the company's B2B initiatives by addressing client-specific use cases and, at times, leading projects end-to-end in partnership with the sales team.
• Design, deploy, and manage Fast API-based microservices for delivering ML models and datasets in production environments.
• Ensure seamless and secure integration with internal platforms and external client systems.
• Partner with senior Data Scientists to improve methodologies, validate model outputs, and speed up knowledge transfer.
• Coordinate with full-stack engineers and DevOps teams to deliver robust, high-performance ML solutions.
• Research and experiment with novel algorithms and multimodal methods, evaluating and implementing leading open-source solutions.

Qualifications

• Minimum of 3 years' experience as a Machine Learning Engineer or Data Scientist, specializing in core ML methods such as classification, clustering, detection, and time-series analysis
• Practical expertise in applying ML to audio, video, text/NLP, and image data, with direct multimodal experience considered a significant advantage
• Advanced Python programming skills with experience developing robust production backends using Fast API
• Demonstrated experience in designing and managing ETL/ETN pipelines for large-scale data ingestion and processing
• Knowledge of JavaScript/TypeScript or openness to learning, enhancing opportunities for cross-stack collaboration
• Enthusiasm for collaborating closely with a senior Data Scientist to develop and implement advanced, cutting-edge solutions
• Highly curious and data-driven, with a passion for building solutions
• Comfortable taking end-to-end ownership of projects, from initial concept and design to full production deployment
• Motivated to drive impact through hands-on execution and problem-solving

This is a unique opportunity to contribute to the development of a next-generation multimodal data infrastructure at a fast-growing, high-impact company backed by leading investors.

Ideally the candidate will be based in Dubai, but we are open to candidates based in wider Middle East, Europe or the US. Asian time-zones will not work for this role.

Salary
: Highly competitive, in line with experience and market standards.

To apply
, please submit your CV via the link.

For additional information about open vacancies and events we are attending, please feel free to follow our LinkedIn Page.

This is a remote position. We represent a technology player whose digital banking platform is transforming financial services in emerging markets making a real impact by embedding credit and savings products into the digital channels people use every day. Their data-driven technology powers MNOs fintechs and banks enabling them to scale fast and drive financial inclusion for millions. For those looking to work on cutting-edge financial tech with real-world impact this is the opportunity for you.

With rapid growth industry recognition and a team that thrives on innovation this is a chance to shape the future of finance in high-growth markets across Africa.

Our client is seeking an exceptional Machine Learning Engineer (Foundation Models Focus) to develop and scale AI and machine learning initiatives across their financial services ecosystem. This role is pivotal in driving AI-powered decision-making automation and hyperpersonalization using foundation models including LLMs and multimodal AI. The Machine Learning Engineer will be responsible for developing pretraining finetuning and optimizing foundation models while working closely with data scientists data engineers and software engineering teams to deploy scalable AI solutions. This position plays a key role in enhancing financial AI applications such as automated underwriting fraud detection credit scoring and AI-powered customer engagement ensuring measurable improvements in performance and customer experience.

• Evaluate scope and support the foundation models and Generative AI strategy including potential applications in automated underwriting alternative credit scoring AI-powered customer interactions fraud detection and early-warning models.
• Design and develop AI-powered applications including chatbots virtual assistants personalized recommendation systems and AI-driven decisionmaking tools.
• Plan for resourcing training and roadmap for AI adoption ensuring alignment with senior management and business needs.

• Pretrain finetune and optimize foundation models (e.g. GPT LLaMA Mistral) for various financial applications.
• Hyperparameter tuning for efficiency (e.g. optimization of transformer architectures Mixture of Experts (MoE) retrieval-augmented generation (RAG)).
• Implement foundation model scaling techniques such as DeepSpeed FSDP and quantization to enhance efficiency.
• Develop custom embeddings tokenizers and retrieval models for enhanced financial NLP and multimodal tasks.
• Build pipelines for prompt engineering reinforcement learning with human feedback (RLHF) and model alignment.

• Work with engineering and data teams to ensure AI Models deployment is scalable secure and cost-efficient.
• Develop efficient inference optimization strategies using ONNX TensorRT and Triton Inference Server.
• Implement MLOps best practices including model versioning continuous monitoring retraining and deployment on on-premise infrastructure or cloud (AWS GCP Azure).
• Define best practices for data collection storage and pipeline automation to enable AI-driven insights in financial services.

• Collaborate with data governance teams to ensure AI models comply with data privacy laws.
• Deploy realtime AI anomaly detection models to mitigate fraud risks in digital transactions.
• Partner with compliance teams to develop AI-driven regulatory reporting tools and automated risk alerts.
• Ensure ethical AI and bias mitigation techniques are integrated into foundation model-based decisionmaking systems.

• Develop AI models for hyperpersonalized financial services based on behavioral analysis and customer interactions.
• Implement AI-powered marketing segmentation dynamic customer scoring and next-best-action recommendation engines.
• Partner with AI research institutions universities and fintech accelerators to drive foundation models and generative AI innovation.
• Represent the company at global fintech and AI summits shaping industry conversations on Generative AI in financial services.
• Publish AI research case studies and thought leadership content to establish the company as a leader in AI-driven fintech.

What it takes to succeed:

• 7 years of experience in AI/ML deep learning NLP or applied machine learning with at least 3 years leading AI teams.
• Strong expertise in foundation models LLM architectures and generative AI.
• Hands-on experience with AI frameworks (PyTorch TensorFlow Hugging Face Transformers DeepSpeed MegatronLM).
• Experience in scaling AI/ML models using distributed computing frameworks (Ray Spark Dask).
• Proven ability to deploy and optimize foundation models in production including quantization distillation and efficient inference strategies.
• Strong knowledge of data governance AI ethics and regulatory compliance (GDPR financial regulations).
• Experience working with vector databases (FAISS Pinecone Chroma) for retrieval-augmented generation (RAG).
• Familiarity with MLOps tools (MLflow Kubeflow Weights & Biases).
• Strong programming skills in Python SQL and cloud platforms (AWS GCP Azure).
• Ability to translate AI innovations into business-driven AI strategies for financial services.