Remote ML Platform Engineer – Mid

Remote ML Platform Engineer – Mid-Level · $95K | RemoteAI ML Platform Engineer Isabella Gomez Full-time · Mid-level · Denver About the role We are the company behind an open source ML experiment tracking and model registry tool with 9,200 GitHub stars and a contributor community of 340 people across 41 countries. Three years ago we were a side project. Two years ago we incorporated. Last year we launched our managed cloud offering and crossed $2M ARR. Our business model is open core: the library stays free and MIT-licensed forever, and we sell managed hosting and enterprise features to organisations that want to run it at scale. The engineering culture here is shaped by the open source project. We write in public. We discuss architectural decisions in GitHub issues before we make them. We merge pull requests from contributors we've never met based on code quality and rationale alone. If that sounds uncomfortable, this is probably not the right place. If it sounds like the way software should be built, you'll feel at home immediately. We're looking for an ML Platform Engineer to work on the infrastructure that powers both the open source project and the managed cloud service. The work spans Kubernetes, CI/CD, observability, and the specific infrastructure challenges of a tool that needs to work identically whether a user runs it on a laptop or at Fortune 500 scale. Responsibilities - Own and improve the Kubernetes infrastructure powering our managed cloud service across GCP - Design and implement CI/CD pipelines for the open source library and the managed product - Build observability into the platform: metrics, tracing, alerting, and on-call runbooks - Contribute to the open source SDK — your platform knowledge should improve the developer experience of the library itself - Review infrastructure contributions from community members and provide constructive technical feedback Requirements - 3–5 years of platform, infrastructure, or ML