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Kayak

19 days ago

Senior ML Ops Engineer

Onsite · Berlin Office

pythondockerkubernetes cost centers

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AI TL;DR

You will design and implement machine learning infrastructure at KAYAK in Berlin. This hands-on role bridges data science and production engineering to ensure reliable ML model deployment.

AI match

Clear role · 80/100 against the market band on this page.

Interview prep for this job

  1. What would you ship in the first month as Senior ML Ops Engineer at Kayak?
  2. Which tradeoff in the description would you ask about first?
  3. How do you explain a production incident to this team?
  4. What would you measure in the first two weeks?
  5. Which part of your last project maps to this stack?

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Job description

You will design and implement machine learning infrastructure at KAYAK in Berlin. This hands-on role bridges data science and production engineering to ensure reliable ML model deployment.

Details

  • Berlin, work from office 3 times a week
  • Experience building and operating ML platforms in production environments
  • Skills: Python, Docker, Kubernetes

The work

  • Build and maintain ML infrastructure end-to-end
  • Own model deployment and serving
  • Develop core MLOps capabilities
  • Improve platform reliability and performance