4Bell Technology

Staffing & Recruiting

Sr ML Engineer(R-1552)

100,000.00-3,100,000.00/A

Any Degree

IT (Information Technology)

Full-time

Abu Dhabi Island And Internal Islands City

20-Jun-2026

Machine Learning LLM GenAI Python PyTorch TensorFlow Scikitlearn Hugging Face Kubernetes. Docker

Job Description

Experience:

• 5+ years of experience in Machine Learning, AI, or Data Science roles with production

deployments.

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, Statistics, Mathematics, or a

related quantitative field.

• Demonstrated success in applying and deploying AI/ML solutions to solve real-world, business-

critical problems.

Technical Expertise

• Strong proficiency in Python with production-quality coding standards.

• Hands-on experience with ML frameworks: PyTorch, TensorFlow, scikit-learn, Hugging Face.

• Experience with LLMs and GenAI Agent design and tooling.

• Experience and deep knowledge of vector databases and services.

• Experience with experiment tracking and MLOps tools: MLflow, Weights & Biases, TensorBoard.

• Solid understanding of SQL and data processing at scale.

• Experience with Kubernetes (AKS).

Deployment & Infrastructure

• Experience with model serving frameworks (vLLM, Triton, TensorRT, ONNX Runtime).

• Hands-on experience with Docker and Kubernetes in production environments.

• Comfortable with setting up CI/CD pipelines for AI/ML workflows.

Soft Skills

• Strong problem-solving and analytical thinking.

• Excellent communication skills with the ability to engage both technical and business

stakeholders.

• Strong stakeholder management and a passion for building high-performing teams.

Nice to Have

• Experience with Azure tech stack, Azure AI Foundry.

• Experience and understanding of working with fine-tuning techniques (LoRA/QLoRA etc.) and

inference optimization tools (vLLM, TensorRT, ONNX Runtime).

• Experience with Data engineering best practices and pipeline creation.

• Healthcare domain knowledge (EHR, FHIR, HL7).

• Experience with GPU optimization, CUDA, or distributed training (DeepSpeed).

• Knowledge of responsible AI practices for AI Agents and services: RAI Guidelines and regulatory

compliance.

• Experience with graph-based ML, reinforcement learning, or federated learning