Lead GCP MLOps Engineer
On-sitePune, Maharashtra, India
Job Summary
Design and maintain scalable MLOps frameworks on Google Cloud Platform to automate the deployment, testing, monitoring, and lifecycle management of Python-based machine learning models. Build automated CI/CD pipelines and infrastructure-as-code solutions for batch and real-time inference workloads using Vertex AI, Cloud Build, and Kubernetes. Implement repeatable deployment processes, artifact governance, and observability dashboards to ensure production-grade reliability and cost efficiency. Troubleshoot platform stability issues and support model retraining, rollback, and release management across development, testing, and production environments.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline
- 5 - 8 years of experience in Cloud Engineering, MLOps, or ML Platform Engineering
- Strong hands-on experience with Google Cloud Platform (GCP)
- Proven experience deploying and operationalizing Python-based machine learning models
- Strong experience with Vertex AI and production ML deployment patterns
- Experience building CI/CD pipelines for machine learning applications
- Experience implementing Infrastructure-as-Code using Terraform or similar tools
- Experience monitoring and supporting production machine learning workloads
- Strong troubleshooting and problem-solving skills
- Google Cloud Platform (GCP)
- MLOps
- Vertex AI
- Model Deployment
- Model Monitoring
- ML Lifecycle Management
- Python
- CI/CD
- Cloud Build
- GitHub Actions
- Jenkins
- GitLab CI/CD
- Infrastructure Automation
- Terraform
- Infrastructure-as-Code
- BigQuery
- Cloud Storage
- Pub/Sub
- APIs
- Cloud Monitoring
- Logging
- Alerting
- Git
- GitHub
Desired Qualifications
- Google Cloud Professional Machine Learning Engineer Certification
- Familiarity with MLflow, Kubeflow, or similar MLOps frameworks
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