MLOps with LLM 23rd May Walk-in drive Bengaluru

Role - MLOps with LLM\nExperience - 4 to 15 years\nInterview Location - Bengaluru\nLocation - PAN INDIA\n\nJob description\nStrong knowledge of MLOps principles and the end-to-end ML lifecycle: data preparation → training → validation → deployment/serving → monitoring/refresh pipelines.\nDesign and implement CI/CD (and CT/continuous training) pipelines for ML workflows, including testing, promotion, rollback, and reproducible builds.\nHands-on with containerization and orchestration (e.g., Docker/Kubernetes) and ML pipeline tooling such as MLflow/Kubeflow (or equivalent).\nMonitoring & observability for ML systems: service + data + model health tracking, drift checks (feature/target/concept), alerts/triggers, and root-cause analysis.\nCloud 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).\nSecurity, governance, and access controls: authentication/authorization, encryption, policy/guardrails, and compliance-focused logging/traceability for production ML.\nCross-functional collaboration with data scientists, engineers, and platform teams to productionize models following best practices for repeatability, standardization, and operational efficiency.\nProficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).