onsite
AI Ops Engineer - Tata Consultancy Services (TCS)
MLOps Engineer
AI Ops Engineer responsible for transforming data science prototypes into production‑grade ML services, building scalable model serving pipelines, and ensuring model reliability with monitoring, drift detection, and automated deployment on cloud platforms.
About the role
Key Responsibilities
- Translate data science prototypes into production‑grade ML services and pipelines.
- Build training and inference code with reproducibility, versioning, and automated testing.
- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
- Collaborate with Data Engineering on feature pipelines and data contracts.
- Own production health: drift detection, performance regression, rollback strategies.
Requirements
- Strong experience in Python and machine learning frameworks (e.g., TensorFlow, PyTorch, scikit‑learn).
- Hands‑on experience with cloud ML services (AWS SageMaker, Lambda, ECS) and containerization (Docker, Kubernetes).
- Proficiency in CI/CD pipelines, version control, and automated testing.
- Knowledge of model monitoring, drift detection, and performance regression techniques.
- Excellent communication skills and ability to collaborate across data science and engineering teams.
Skills
pythonmachine learningawsdockercicd