Backed by E14 Fund.
About the role
We're hiring an ML Infrastructure Engineer to own the infrastructure and tooling that our research team runs on every day. This is a hybrid DevOps / Developer Experience role: you'll stand up and operate large GPU clusters, build data pipelines that move massive medical datasets through training jobs efficiently, and create the tooling that lets our researchers move fast without thinking about plumbing ML Infrastructure Engineer Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Observability and on-call. Grafana dashboards, structured alert tiers routed through Slack and PagerDuty. Catch problems before researchers do
- Reliability culture. Postmortems, runbooks, sane defaults. The bar is that no researcher is ever blocked on infrastructure for more than a few minutes
- Comfort across the stack: Linux, Python, Kubernetes or equivalent orchestration, at least one major cloud (AWS / GCP / Azure), CI/CD
- A genuine developer-experience instinct. You treat researchers as your primary users, and you measure success by how invisible the infrastructure becomes
- Solid software engineering fundamentals — you can build tooling that other engineers rely on, with tests, docs, and a sane API
- Production experience with SkyPilot, lakeFS, or W&B
More about this role
We're hiring an ML Infrastructure Engineer to own the infrastructure and tooling that our research team runs on every day. This is a hybrid DevOps / Developer Experience role: you'll stand up and operate large GPU clusters, build data pipelines that move massive medical datasets through training jobs efficiently, and create the tooling that lets our researchers move fast without thinking about plumbing ML Infrastructure Engineer
About Voio
Voio is a healthcare AI company building frontier foundation models for medicine. We're based in San Francisco and our research team trains on extremely large multimodal medical datasets. The infrastructure this role owns goes directly into models aimed at improving clinical decision-making at scale.
The Role
We're hiring an ML Infrastructure Engineer to own the infrastructure and tooling that our research team runs on every day. This is a hybrid DevOps / Developer Experience role: you'll stand up and operate large GPU clusters, build data pipelines that move massive medical datasets through training jobs efficiently, and create the tooling that lets our researchers move fast without thinking about plumbing.
If you've ever sat next to an ML...
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