Technology
Pune
About the job
Role Summary
We are seeking a highly skilled Senior GCP MLOps Engineer to support the deployment, automation, and operationalization of machine learning solutions on Google Cloud Platform (GCP).
The primary focus of this role is to automate the deployment and lifecycle management of Python-based machine learning models developed by business and data science teams. The ideal candidate will possess strong expertise in GCP cloud engineering, MLOps frameworks, CI/CD automation, infrastructure management, and production-grade ML deployment architectures.
This is an engineering-focused role responsible for ensuring machine learning models are deployed, monitored, scalable, secure, and reliable in production environments.
Key Responsibilities
1. MLOps Platform Engineering
- Design, build, and maintain scalable MLOps frameworks on Google Cloud Platform.
- Automate deployment, testing, monitoring, and lifecycle management of machine learning models.
- Establish repeatable and standardized ML deployment processes across environments.
- Implement model versioning, artifact management, and deployment governance standards.
- Support model retraining, rollback, and release management processes.
2. Machine Learning Deployment & Automation
- Deploy Python-based machine learning models into production environments.
- Build automated deployment pipelines for batch and real-time inference workloads.
- Develop reusable deployment templates and automation frameworks.
- Support model serving using Vertex AI Endpoints and containerized deployment architectures.
- Ensure high availability, reliability, and scalability of production ML services.
3. CI/CD & Infrastructure Automation
- Design and implement CI/CD pipelines for machine learning applications and services.
- Integrate source control, testing, and deployment workflows into enterprise delivery pipelines.
- Implement Infrastructure-as-Code (IaC) practices for repeatable workplace provisioning
📌 Lead GCP MLOps Engineer (Pune)
🏢 Merkle
📍 Pune