Lead MLOps Engineer
Building scalable AI/ML infrastructure, automation pipelines, and self-hosted platforms.
I design and run infrastructure for ML and software teams: from reproducible environments and delivery pipelines to automation that keeps production systems predictable.
- Lead MLOps and DevOps work across automation, CI/CD, observability, and self-hosted services.
- Build practical tools in Python and C# when existing systems need glue, guardrails, or a clean operator experience.
- Keep infrastructure explicit with Terraform, Ansible, containers, and repeatable deployment flows.
- Prefer boring reliability, clear ownership, and systems that can be debugged at 03:00 without guesswork.
| Project | What it does | Stack |
|---|---|---|
| Cleanarr | Cascade media cleanup for Radarr, Sonarr, Jellyseerr, qBittorrent, and Jellyfin. | Python, automation |
- MLOps platforms: reproducible environments, deployment pipelines, and model-serving infrastructure.
- Automation: CI/CD, GitOps, release flows, and routine operations with fewer manual steps.
- Self-hosted systems: observable, maintainable services that can be debugged quickly.
- Developer tooling: small CLIs, integrations, and internal tools that remove operational friction.