Senior Machine Learning Engineer

Job Post :- Senior Machine Learning EngineerExperience - 5+ yearsLocation - Ahmedabad (Remote) (You need to relocate onsite Abu Dhabi)Experience:• 5+ years of experience in Machine Learning, AI, or Data Science roles with productiondeployments.• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, Statistics, Mathematics, or arelated 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 businessstakeholders.• 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.) andinference 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 regulatorycompliance.• Experience with graph-based ML, reinforcement learning, or federated learning.

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