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MLOps Reliability Engineer

Ava Nakamura

Full-time · Job · Los_Angeles

About the role

We just crossed a major usage milestone and our model-serving infrastructure is starting to show cracks under the load. We need a senior MLOps engineer who can walk into that mess and make it boring again — stable deployments, predictable rollbacks, and monitoring that actually catches problems before customers do. Fast-moving team, real production stakes. You'll own the Kubernetes and MLflow setup end to end, with the authority to make the infrastructure calls that keep our growth curve from breaking things. Ship fast, but ship things that stay up.

Responsibilities

  • Own model deployment infrastructure on Kubernetes and AWS
  • Harden the MLflow-based model registry and versioning workflow
  • Build monitoring and alerting for model serving reliability
  • Reduce deployment failure rates through better rollback tooling
  • Lead incident response for production model issues

Requirements

  • 5+ years in MLOps or infrastructure engineering
  • Deep hands-on experience with Kubernetes and Docker in production
  • Familiarity with MLflow or comparable model registry tools
  • Strong Python skills for tooling and automation
  • Comfortable owning infrastructure decisions with real stakes

Benefits

  • Fully remote position
  • Equity in an early-stage, fast-growing company
  • Health and dental insurance
  • Home office stipend
  • Unlimited PTO

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Categories

MLOps & AI Infrastructure

Skills

docker kubernetes mlflow aws python

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

docker kubernetes mlflow aws python

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