H
MLOps Engineer
Hugo Lindqvist
Full-time · Mid-level · New_York
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
Job Type
Full-time
Level
Mid-level
Language
English
Salary Range
$90,000 – $115,000
AI Expertise
MLOps & AI Infrastructure
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