Senior ML Ops Engineer

7 - 12 years

30 - 45 Lacs

Posted:4 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description


We are looking for a Senior MLOps Engineer to join our team. This is a dedicated MLOps position with a strong focus on operational responsibilities. You will be responsible for operationalizing machine learning solutions, managing infrastructure monitoring, ensuring observability, and maintaining robust CI/CD pipelines.

You will work closely with software engineers, data scientists, and DevOps teams to build and scale core MLOps infrastructure that powers AI initiatives across the organization.

Key Responsibilities

  • Design, develop, and maintain end-to-end MLOps pipelines to automate the ML lifecycle from training to deployment and monitoring.
  • Collaborate with data scientists, ML engineers, and platform teams to operationalize ML models across cloud and hybrid environments.
  • Build and manage containerized environments for training and inference using Docker and Kubernetes.
  • Implement CI/CD workflows (GitHub Actions, Jenkins) for deploying ML models.
  • Ensure observability and monitoring of models in production (latency, drift, performance, errors) using Prometheus and Grafana.
  • Support model deployment to APIs, applications, dashboards, and edge devices.
  • Implement model versioning, rollback strategies, governance, and traceability using tools like MLflow or Kubeflow.
  • Drive best practices and provide technical mentorship on MLOps topics.
  • Continuously evaluate and integrate new tools and technologies to improve MLOps capabilities.

Required Skills & Qualifications

  • 8+ years of experience in software, data, or ML engineering, with 6+ years in MLOps.
  • Must have a full-time graduation degree in Engineering (B.Tech/B.E).
  • Strong programming experience in Python, SQL, Spark/PySpark.
  • Deep expertise in MLOps tools such as MLflow, Kubeflow, Airflow.
  • Hands-on experience with GCP (Vertex AI, GKE, Cloud Run) mandatory.
  • Proficient with Databricks, FastAPI, Docker, Kubernetes.
  • Strong knowledge of CI/CD, Git, Infrastructure as Code (Terraform, Ansible).
  • Familiarity with monitoring frameworks like Prometheus and Grafana.
  • Excellent communication and stakeholder management skills

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