Cursor
Engineering Manager, ML
San Francisco
Sponsorship not specifiedDetected 12 days ago
Distributed SystemsMachine LearningResearchMentoring
About the role
- Designing eval pipelines that catch regressions before they ship, and give researchers fast, trustworthy signal on whether a change actually helped.
- Owning the environments in which models are trained and tested: sandboxed, reproducible, and fast enough that iteration speed isn't the bottleneck.
- Bringing rigor to how the team measures quality and progress, in places where "did it ship" isn't the same as "did it work?"
Responsibilities
- The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering.
- Building the rollout infrastructure that lets researchers run RL experiments at scale without fighting the plumbing.
- We're hiring across a range of scope for this role, depending on experience and the size of problem you're ready to own.
Nice to have
- hands-on experience with RL training infrastructure, eval frameworks, or building and maintaining simulated environments for model training or testing.
Benefits
- Bonus: hands-on experience with RL training infrastructure, eval frameworks, or building and maintaining simulated environments for model training or testing.
Company info
- You've led engineering teams building infrastructure that trains, evaluates, or serves ML models in production.
- Our mission is to automate coding.
This listing is sourced directly from Cursor's careers page and normalized into a canonical job model.