AI Engineer (World Models)

Why are We Hiring for this Role:

We are building a general-purpose humanoid that must understand and navigate the physical world — and that requires a dedicated engineer to architect the internal models that make that possible

World models are the cognitive backbone of our robot; without them, the humanoid cannot plan, predict, or adapt to novel environments

We are at an inflection point where our hardware is ready — now we need the intelligence layer to match it

The gap between a robot that executes fixed commands and one that truly reasons about its environment is a world model; we are hiring to close that gap

As we scale to real-world deployment, our humanoid needs to generalize across unstructured, unpredictable settings — something only a robust world model can enable

This hire will directly shape the core intelligence architecture of our platform before it becomes locked in at scale

What Kind of person are we looking for

Hands-on experience building world models, model-based RL, or predictive world simulators using frameworks like PyTorch or JAX — you have shipped these systems, not just studied them

Strong foundation in deep learning architectures relevant to world modeling: transformers, diffusion models, neural radiance fields (NeRF), and variational recurrent state-space models

Proficient in Python as a primary research and development language, with production-level familiarity in C++ for latency-sensitive inference and real-time robotics integration

Experience with robotics middleware and simulation environments — ROS2, Isaac Sim, MuJoCo — and the ability to close the sim-to-real gap in learned representations

Experience with video prediction or future-frame generation models (e.g., RSSM, DreamerV3, UniSim, Genie) is a strong plus

Able to read and implement from recent arXiv papers with minimal overhead — you are comfortable turning a research prototype into a tested, integrated syste