Senior ML Ops Engineer

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