Senior Machine Learning Engineer - AI

Job Post :- Senior Machine Learning Engineer Experience - 5+ years

Location - Ahmedabad (Remote) (You need to relocate onsite Abu Dhabi)

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.