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
- Robust 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.

📌 AI/ML Engineer – MLOps (Hyderabad)
🏢 PineQ Lab Technology
📍 Hyderabad