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MLOps Engineer

Chase Pham

Full-time · Job · Chicago

About the role

Kubernetes, Airflow, and Docker are the core of what we build. If you enjoy making other engineers' models actually run reliably in production, this role is for you. You'll harden our deployment pipelines, standardize how models move from training to serving, and reduce the operational overhead our on-call team carries. Our clients include enterprise operations teams where uptime and auditability are non-negotiable, so the systems you build need to be boring in the best possible way.

Responsibilities

  • Build and maintain CI/CD pipelines for model training and deployment
  • Standardize containerized packaging for models across teams
  • Own uptime and alerting for production inference services
  • Partner with data scientists to reduce deployment friction
  • Document deployment runbooks for the on-call rotation

Requirements

  • 3+ years in MLOps, DevOps, or platform engineering
  • Strong hands-on experience with Kubernetes and Docker
  • Experience orchestrating pipelines with Airflow or similar tools
  • Comfortable working within AWS-based infrastructure
  • Track record of improving deployment reliability

Benefits

  • Fully remote position
  • Competitive salary
  • 401k matching
  • Health and dental insurance
  • Home office stipend

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Categories

MLOps & AI Infrastructure

Skills

python airflow docker kubernetes aws

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python airflow docker kubernetes aws

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