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.