Lead ML Devops Engineer
DGS India - Pune - Kharadi EON Free Zone
INR 3000K-5000K (estimate) Senior-level Full Time
Tasks
- Automate deployment testing monitoring and lifecycle management
- Build automated deployment pipelines for batch and real time inference
- Create reusable deployment templates and automation frameworks
- Deploy Python machine learning models to production
- Design and support cloud native ML infrastructure on GCP
- Design build and maintain MLOps frameworks on GCP
- Design implement CI CD pipelines for ML applications
- Ensure availability reliability and scalability of ML services
- Establish logging observability and operational dashboards
- Establish standardized ML deployment processes
- Implement Infrastructure as Code for environment provisioning
- Implement model versioning artifact management and deployment governance
- Implement monitoring and alerting for ML services
- Integrate source control, testing, and deployment workflows
- Manage development, testing, and production environments
- Optimize services for performance reliability security and cost
- Serve models with Vertex AI Endpoints and containers
- Support model lifecycle governance and operational compliance
- Support retraining rollback and release management
- Track model performance operational health latency and utilization
- Troubleshoot production issues and support platform stability
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Alerting | BigQuery | CI/CD | Cloud Build | Cloud Monitoring | Cloud Run | Cloud Storage | Cloud platform | Git | GitHub Actions | GitLab CI | GitLab CI/CD | Google Cloud | Google Cloud Platform | Infrastructure as Code | Jenkins | Kubernetes Engine | Logging | MLOps | Pub/Sub | Python | Terraform | Vertex AI | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Technology
Roles
Engineer | GCP MLOps Engineer | Lead | Lead MLOps Engineer | MLOps Engineer
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