- New York, New York, United States
- On-site
- Full-time · Staff
- 8+ years
Setting the research agenda for Hardware Intelligence, building agents that reason over hardware context, and leading the post-training of AI models.
Responsibilities
- Set the research agenda for Hardware Intelligence: pick the problems, place the bets, and define what winning looks like each quarter.
- Figure out how to store and represent hardware context, so agents reason over telemetry, test campaigns, requirements, designs, and simulations instead of retrieving them.
- Teach agents to work the tools engineers already use, from CAD to simulation to analysis software, through computer use.
- Connect simulation to the physical world: calibrate simulations against measured results, and use simulations to plan and explain tests.
- Build distributed intelligence: collections of agents that coordinate across programs, fleets, and teams.
Requirements
- Nice to have: post-training at a frontier lab
- Nice to have: computer-use agents
- Nice to have: multi-agent systems
- Nice to have: knowledge representation
- Nice to have: scientific ML