Job Description :

Role : ML DevOps Engineer

Work Location : Pune / Mumbai / Gurugram / Bangalore.

Work Mode : Hybrid (1:00 PM - 10:00 PM)

Interview Rounds : 3 Rounds (Virtual)

Responsibilities :

- Design, build, and maintain scalable MLOps pipelines on GCP.

- Develop and deploy ML models using Vertex AI.

- Automate model training, deployment, monitoring, and retraining workflows.

- Build CI/CD pipelines for ML applications and services.

- Manage containerized deployments using Docker and Kubernetes.

- Implement Infrastructure as Code (Terraform) and cloud automation.

- Monitor model performance, drift, and production health.

- Collaborate with Data Scientists, ML Engineers, and Data Engineers to productionize ML solutions.

- Optimize cloud infrastructure for reliability, scalability, and cost efficiency.

- Ensure security, governance, and best practices across ML platforms.

Preferred Qualifications :

- Experience with Vertex AI Pipelines, Feature Store, and Model Registry.

- Hands-on experience with GenAI/LLMs, RAG, Gemini, or Agentic AI.

- Exposure to BigQuery, Cloud Run, Dataflow, GKE, and Cloud Composer.

- Strong understanding of ML lifecycle, model monitoring, and observability.

Key Skills :

- Python, Google Cloud Platform (GCP), Vertex AI, MLOps, Docker & Kubernetes, CI/CD (GitHub Actions, Jenkins, Cloud Build), Terraform, BigQuery, MLflow / Kubeflow, SQL.

Education :

- UG: Any Graduate

Preferred Skills :

- GCP Cloud, Vertex Ai, ML DevOps, ML Deployment, Jenkins, DevOps, Development and Deployment, Docker, Ci/Cd, ML Flow, Machine Learning, Kubernetes.