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AI Release Automation Engineer

Aurora Vestergaard

Contract · Job · Berlin

About the role

Our model deployment pipeline still requires someone to manually check a checklist before every release, and that checklist keeps growing every time something breaks in production. Our clients include teams who can't tolerate a bad model release reaching their production traffic, so the release process, while slow, has never been allowed to skip steps. Your job is to automate that checklist into a proper pipeline using Docker, Kubernetes, and MLflow, deployed on Azure. This is a contract role with a clearly scoped deliverable: an automated release pipeline that replaces the manual checklist within ten weeks.

Responsibilities

  • Automate the manual model release checklist into a pipeline
  • Use MLflow to track which model versions passed which checks
  • Deploy the automated pipeline on Azure using Docker and Kubernetes
  • Document the new process for the platform team to maintain

Requirements

  • 1-2 years of experience with Docker and Kubernetes
  • Basic Python scripting for automation tasks
  • Exposure to MLflow or similar tracking tools is a plus
  • Comfortable working within a fixed ten-week contract scope

Benefits

  • Fully remote engagement
  • Flexible hours
  • Possible extension based on delivery

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Categories

MLOps & AI Infrastructure

Skills

python docker kubernetes mlflow azure

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Job Type

Contract

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python docker kubernetes mlflow azure

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