Job Description

What youll be doing

  • Maintain and enhance existing ML pipelines in AWS with a focus on Infrastructure as Code using CloudFormation.
  • Implement minimal but essential pipeline extensions to support ongoing data science workstreams.
  • Document infrastructure usage, architecture, and design using tools like Confluence, GitHub Wikis, and system diagrams.
  • Act as the internal infrastructure expert, collaborating with data scientists to guide and support model deployments.
  • Research and implement optimization strategies for ML workflows and infrastructure.
  • Work independently and collaboratively with cross-functional teams to support ML product

What do we need from you

  • 5+ years of hands-on DevOps experience with AWS Cloud.
  • Proven experience with at least two MLOps projects deployed using SageMaker or similar AWS services.
  • Strong proficiency in AWS services: SageMaker,...

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