Build the Future of Fabrication — Design Intent to Chip
Help us replace today’s manual design-to-manufacturing translation with programmable manufacturing intelligence. We're a team of fab engineers, physicists and AI engineers
Engineering expertise as infrastructure
AIMS lets fab engineers build Physics Enhanced Digital Twins of their tools and processes, then use them to generate recipes, design smarter DOEs, and explore process space 24/7. The long-term direction is to build the system that enables living in a world where everyone can fabricate their own Chip
Models are constrained by fab physics and validated on production data. Your work ships to a fab, not a slide
People who have developed and executed fabrication processes sit next to people who have built software and trained AI models.
Small team, on-prem product, demanding customers. You'll own problems end to end and see them land in a fab.
Engineers who want to learn the other half
MOCVD, epitaxy, lithography, etching, deposition, metrology, process integration, etc. You've developed recipes the hard way and want the next generation to develop them faster. We'll teach you AI.
Physics-informed ML, surrogate modeling, Bayesian optimization, ML systems that run on-prem. You want sparse, expensive, physical data instead of another web-scale dataset. We'll teach you the fab.
Current openings
When applying, please submit no more than two pages describing three outcomes related to the role you are applying for that you are most proud of.
If you do not have direct experience in the specific role but are still interested, please apply if you can demonstrate three relevant outcomes in the field.
Don't see your role? Write to us anyway; we are always looking for smart capable colleagues that believe in our vision.
Small team. Real constraints. Honest results.
Everything runs on-prem behind a customer's firewall. We optimize for what works on their tool, not what demos well.
Held-out validation before anything is called a result. Roadmap items are labeled as roadmap. No faked metrics, internally or externally.
Fab and AI engineers learn fastest at the same whiteboard. Given that talents come from all over the world we use modern tools to share ideas, learn and accelerate development
Think you belong on the bridge?
Send a note and what you've built. An engineer reads every application.