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Requirements:
- 10+ years of experience with at least 7+ years of AWS cloud transformation & DevOps
- Experience in designing, deploying, and managing end-to-end machine learning (ML) lifecycles using Amazon SageMaker
- Designing and maintaining CI/CD pipelines for ML, containerizing models with Docker, and setting up SageMaker endpoints
- Monitoring model health, managing infrastructure, and ensuring data governance
- A strong understanding of evolving DevOps, SRE, Observability ecosystem in the context of hybrid cloud
- Defining persona-based roles with SageMaker Role Manager, creating SageMaker Unified Studio domains/user profiles, and managing VPC configurations.
- 5 + years AWS Architecture experience is highly desirable
- AWS Solution Architect certification is highly desirable