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MLOps Engineer

Hugo Lindqvist

Full-time · Mid-level · New_York

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About the role

The numbers: 12 ML models in production, 6 of them retrained weekly, 3 teams with conflicting deployment processes, 0 shared model registry, and 1 MLOps engineer (currently) handling everything. We are hiring a second MLOps engineer to help build the infrastructure that scales. This is not a glamorous greenfield role — it's fixing what exists, building standards, and making it survivable for a team that is growing fast. If you like turning operational chaos into working systems, come talk to us.

Responsibilities

  • Stabilise and expand our CI/CD pipelines for model training and deployment
  • Set up a shared model registry and enforce versioning standards across teams
  • Build monitoring for model performance and data drift
  • Document our infrastructure and create onboarding guides for new ML engineers
  • Work with data engineers on pipeline orchestration improvements

Requirements

  • 2–4 years MLOps with at least one production ML system owned end to end
  • Hands-on experience with Airflow and MLflow (or comparable alternatives)
  • Docker and basic Kubernetes — comfortable deploying containerised services
  • Cloud experience (GCP, AWS, or Azure)
  • Able to write clear documentation and enforce standards across teams

Benefits

  • High-impact engineering role
  • Remote-first
  • $90,000 – $115,000
  • Equity
  • Flexible schedule with 10:00–15:00 EST core hours

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Categories

MLOps & AI Infrastructure

Skills

python kubernetes mlflow airflow ci/cd

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Job Type

Full-time

Level

Mid-level

Language

English

Salary Range

$90,000 – $115,000

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes mlflow airflow ci/cd

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