Key Responsibilities
- Build and maintain ML operations infrastructure and pipelines
- Automate model training, testing, and deployment processes
- Implement monitoring and logging for production ML systems
- Optimize model performance and resource utilization
- Ensure reliability and scalability of ML deployments
Required Qualifications
- 5+ years in DevOps/MLOps with production ML experience
- Expertise in containerization and orchestration (Docker, Kubernetes)
- Strong knowledge of CI/CD pipelines and automation tools
- Experience with cloud platforms (Azure, AWS, GCP)
- Proficiency in Python and infrastructure-as-code
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