ML · physics
ABOUT VINCI
Every physical thing you touch exists because somebody successfully navigated the laws of physics: the chips in your phone, the vehicles on the road, the data centers powering AI. Physics determines what can be built, how well it performs, and where it breaks. Yet the tools engineers use to understand physical behavior are too slow and too specialized to use continuously while designing, so critical decisions get made with only a partial view of how a system will behave.
Our mission is to make physical reasoning as accessible to engineers as language became through modern AI. This is not an attempt to build slightly better engineering software. It is an attempt to change how physical products are designed. Our technology is used today by many of the world's most advanced semiconductor and electronics organizations, including nearly half of the twenty largest companies in the industry. We are backed by Khosla Ventures and Eclipse Ventures.
THE ROLE
Our foundation model learns physics from simulations, and we generate the simulation data ourselves. The simulations encapsulate real-world, validated physical results. Our aim is to create a data corpus covering multiple types of physics over an exhaustive set of physical objects.
Our data corpus is expanding. We currently operate on the petabyte scale, and our data volume is growing rapidly. We are hiring the engineer who makes that possible: the person who owns the pipeline from "here is a generation recipe" to "here is a versioned, validated dataset a training run can consume," and the ML lifecycle around i