Tata Consultancy Services
Website:
tcs.com
Job details:
Role - MLOps with LLM
Experience - 4 to 15 years
Interview Location - Bengaluru
Location - PAN INDIA
Job description
- Strong knowledge of MLOps principles and the end-to-end ML lifecycle: data preparation → training → validation → deployment/serving → monitoring/refresh pipelines.
- Design and implement CI/CD (and CT/continuous training) pipelines for ML workflows, including testing, promotion, rollback, and reproducible builds.
- Hands-on with containerization and orchestration (e.g., Docker/Kubernetes) and ML pipeline tooling such as MLflow/Kubeflow (or equivalent).
- Monitoring & observability for ML systems: service + data + model health tracking, drift checks (feature/target/concept), alerts/triggers, and root-cause analysis.
- Cloud platform experience (AWS/Azure/GCP) to deploy and run ML workloads using managed services and cloud-native components (e.g., GKE, BigQuery, Cloud Storage, Vertex AI capabilities).
- Security, governance, and access controls: authentication/authorization, encryption, policy/guardrails, and compliance-focused logging/traceability for production ML.
- Cross-functional collaboration with data scientists, engineers, and platform teams to productionize models following best practices for repeatability, standardization, and operational efficiency.
- Proficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).
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