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Tcs Hiring | ML Ops Developer | Kolkata - Face To Face Interview

Tata Consultancy Services · Kolkata, West Bengal, India

3–9 yrs experiencefull_timePosted 1w ago
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Job description

**Job description** **TCS Hiring | ML Ops Developer | Kolkata | 5 to 12 Yrs | Face to Face Interview** Exciting Opportunity with **Tata Consultancy Services (TCS)!** **We are hiring experienced ML Ops Developer for a Face-to-Face Walk-in Drive in Kolkata.** **Interview Details** **Date: 11th July 2026 (Saturday)** **Mode: Face-to-Face Interview** **Location: Kolkata** **Experience: 5 to 12 Years** **Role: ML Ops Developer** We are looking for passionate engineers who thrive in a fast-paced environment and are eager to build scalable, cloud-native applications. **Job description:** **Technical/Functional Skills:** - 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).