San Francisco, CA - ONSITEWe're building the intelligence layer for physical risk: digital twins of individual homes, run through physics-informed AI World Models, to see exactly how a specific property will perform in a wildfire or hurricane — traditional models only guess at the neighborhood level.

We're building the intelligence layer for physical risk: digital twins of individual homes, run through physics-informed AI World Models, to see exactly how a specific property will perform in a wildfire or hurricane — traditional models only guess at the neighborhood level. That precision lets us do what insurers historically couldn't: measure how much a new roof, cleared vegetation, or better siding actually cuts risk, then price coverage accordingly, turning mitigation into a real financial incentive instead of just advice.

We've scaled to ~$10B in insured assets in just two states in under a year. The interesting problems: ML surrogates that run physics simulations 1,000x+ faster without losing accuracy, structure-level digital twins built from imagery and property data at scale, and systems that reason across risk, cost, and homeowner tradeoffs — we're hiring across engineering and applied science.

Open Roles:

Member of the Technical Staff, AI Harness (Full-time, Hybrid, $270-325k, Offers Equity) - https://www.standinsurance.com/careers/259bb94f-1dfd-458f-88...