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.

- Valuable 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.

📌 AI/ML Engineer – MLOps (Hyderabad)
🏢 PINEQ LAB
📍 Hyderabad