Research Engineer, World Models & Simulation

About the role

Orbifold AI is building the infrastructure layer for Physical AI. As intelligent systems move beyond language into the physical world, they require a fundamentally new understanding of physics, action, and interaction. We partner with leading robotics and world model research teams to advance the foundations of embodied intelligence, enabling intelligent systems to perceive, understand, and operate in the real world. The standards we set, and the infrastructure we build to scale them, will define the next frontier of robotics and Physical AI.

To grade a robot policy you need an environment that is both varied and accurate, and nothing available today is both. Testing on a real robot is accurate and covers almost nothing, a few dozen trials, a broken arm, a room that never resets the same way twice. Hand-built simulators run cheaply but can only show you what somebody already modeled by hand, so the variety stops where the asset library stops. Web video has endless variety and no measured physics at all. You will fill the empty quadrant. Learned world models, trained on a corpus of real captured experience that is reconstructed rather than estimated, good enough that a partner’s policy can be rolled out thousands