- Role: ML DevOps Engineer
- Work Location : Pune /Mumbai/ Gurugram /Bangalore.
- Work Mode: Hybrid (1:00 PM - 10:00 PM)
- Interview Rounds: 3 Rounds (Virtual)
- Experience: 510 Years

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.
- Solid 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

Reach out to [email protected] or whatsapp : (phone hidden)

📌 ML DevOps Engineer / Lead ML Ops Engineer (Pune)
🏢 Talent Drive Consulting
📍 Pune