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AI Canary Deployment Specialist

Lumio Systems

Remote · Under $60k / year · Part-time · Posted 5 months ago

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About the role

Deploying a new model version to 100% of traffic is gambling. Canary deployments route 5% of traffic to the new version first, compare its behavior against the old version, and only promote if the new model performs equal or better. But someone needs to define what 'better' means, monitor the comparison metrics, and make the promotion decision. This part-time role (20h/week) focuses on canary deployment management for our ML platform: configuring traffic splits for model canary releases, monitoring comparison dashboards during canary periods, documenting deployment outcomes, and building the automated promotion rules that eventually replace manual decisions. Canary deployments are the safety net between development and production. You'll learn how ML models behave differently in production versus testing, what metrics actually predict production success, and how to catch regressions before they affect all users.

Fully remote.

Responsibilities

  • Configure traffic splits for model canary release deployments
  • Monitor comparison dashboards during canary evaluation periods
  • Document deployment outcomes and model version performance differences
  • Build automated promotion rules based on canary evaluation criteria
  • Escalate canary failures with diagnostic information for ML teams

Requirements

  • Python proficiency with basic infrastructure knowledge
  • Familiarity with Docker and Kubernetes concepts
  • SQL skills for querying deployment metrics
  • Interest in MLOps and deployment reliability
  • Available for 20 hours/week

Benefits

  • Part-time (20h/week) with flexible scheduling
  • Fully remote — European time zones
  • Learn production ML deployment practices
  • Option to expand to full-time

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Categories

MLOps & AI Infrastructure

Skills

python docker kubernetes mlflow sql

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Salary Range

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AI Expertise

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Skills

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