Founding Machine Learning - World Models

We build world models that simulate manipulation scenes faithfully enough to validate, and one day, train policies without touching a robot. You'll develop generative models that make this work, with the controllability and physical fidelity to match real-robot behavior.

**What you'll do:**

* **Train video and dynamics models:** Develop world models with action conditioning for manipulation policies. * **Push long-horizon coherence:** Develop architectures and training methods that extend rollout quality on hard physical tasks. * **Own training infrastructure:** Run multi-GPU clusters, write custom CUDA, debug at scale. * **Build the world-model data engine:** Design, implement, and improve a data engine that allows the world model to compound learning across customers and manipulation tasks.

**Requirements:**

* Very strong coding in Python and PyTorch (or similar). * **Video generation experience:** Deep experience training image or video generation models end-to-end. * **Large-scale training:** Track record operating training runs at cluster scale. * **3D vision:** Working knowledge of multi-view geometry, scene reconstruction, and physical priors.