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AI Platform Support Engineer

Aurora Vestergaard

Full-time · Job · Chicago

About the role

Our mission is zero-surprise deployments for every model our clients push to production. Docker, Kubernetes, MLflow, and Airflow are the core of what we run. If you like keeping infrastructure boring and predictable, this role is for you. You'll be the senior escalation point when deployment pipelines misbehave, working across AWS-hosted clusters to diagnose issues fast and prevent repeat incidents. Fast-moving team. Big problem. We need someone who ships fixes, not just tickets.

Responsibilities

  • Serve as senior escalation point for deployment pipeline incidents
  • Maintain and improve MLflow and Airflow infrastructure on AWS
  • Document recurring failure patterns and drive permanent fixes

Requirements

  • Deep hands-on experience with Docker, Kubernetes, and AWS in production
  • Experience with MLflow or similar ML pipeline orchestration tools
  • Strong incident response and root-cause analysis skills

Benefits

  • Fully remote position
  • On-call compensation on top of base salary
  • Equity and annual bonus

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Categories

MLOps & AI Infrastructure

Skills

docker kubernetes mlflow airflow aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

MLOps & AI Infrastructure

Skills

docker kubernetes mlflow airflow aws

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