AI/ML Engineer – MLOps

Role- AI/ML Engineer MLOps & LLMOps

Experience: 5+ Years

Must Have: Machine Learning Operations (MLOps) Key Responsibilities

• Design, build and maintain ML/LLM pipelines for training, fine-tuning, evaluation and deployment.
• Operationalize LLM solutions from experimentation to production environments.
• Build and monitor observability for LLM applications, including latency, throughput, hallucinations, drift and prompt performance.
• Implement RAG workflows, prompt management and versioning.
• Automate model validation, testing and CI/CD pipelines.
• Ensure security, compliance and data governance for AI/ML solutions.
• Design and optimize infrastructure required for MLOps/LLMOps.
• Work with cloud-based AI services and multi-cloud environments.

Must-Have Skills

• Strong hands-on experience in MLOps / Machine Learning Operations.
• Advanced Python skills.
• Strong understanding of LLMOps infrastructure and deployment.
• Experience with ML/LLM pipelines and productionization.
• Knowledge of RAG, LLM evaluation, monitoring and observability.
• Experience with machine learning frameworks.
• Good exposure to cloud AI services.
• Multi-cloud experience.

Good to Have

• Experience with LLM serving frameworks and infrastructure.
• Experience with model optimization and production deployment.
• Knowledge of AI security, governance and responsible AI practices.

Note: The role focuses on building production-ready AI/ML and LLM solutions , with strong emphasis on MLOps, LLMOps, cloud and operational excellence.