ML Infra, Simulation Engineering

You will own the simulation our robots are trained and tested in. That means making it fast enough to run large-scale training, accurate enough that results transfer to hardware, and honest enough that we know which results to trust.

Simulation is only useful if it predicts reality. You will own both halves of that: the performance that makes large-scale training possible, and the fidelity that makes the results mean something.

• Own our simulation stack: physics, rendering, scene generation, and the interfaces training and evaluation run against.
• Drive simulation throughput, including GPU-accelerated and massively parallel rollouts, so training is not bottlenecked by the simulator.