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Key Responsibilities:

  • Design, build, and automate enterprise-grade AWS SageMaker environments for scalable ML.
  • Develop DevOps automation for SageMaker Unified Studio and cloud infrastructure.
  • Configure lifecycle configurations and optimize CI/CD pipelines.

Requirements:

  • 6+ years in DevOps, Cloud Engineering, or related field.
  • Expert-level AWS and Python experience.
  • Strong hands-on with SageMaker and ML infrastructure.

Benefits:

  • Fully remote within Europe.
  • Flexible engagement as contractor or employee.
  • Work on cutting-edge AI and cloud projects.

Why Apply:

  • High-impact role with advanced AWS and MLOps.
  • Collaborative international team.
  • Opportunities for professional growth.

Jobgether

This role is listed on behalf of a partner company that builds and optimizes enterprise-scale machine learning infrastructure. They operate with a collaborative international team and modern engineering practices.

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