Machine Learning: World Models

- Architect Neural Simulators: Design and train spatiotemporal models that move beyond short clips toward coherent, long-form world simulations.

- Scale Training: Own the end-to-end training of multi-billion parameter models on huge clusters.

- Own the Training Loop End-to-End: Design, run, debug, and iterate on large-scale training experiments-diagnosing failure modes, improving data mixtures, and tightening evaluation to drive measurable gains.

- Very strong coding skills in Python, C++, or Rust.

- Video Generation Expertise: Deep experience shipping/researching high-fidelity video models.

- Architectural Intuition: Ability to design from scratch and reason about scaling laws and failure modes.

- Infrastructure Fluency: Comfortable managing and optimizing large-scale experiments on massive GPU clusters.

You'll work with a small, elite team on challenges that require speed, intelligence, and deep engineering instinct. If you enjoy understanding systems at all levels, move fast, and think even faster, you'll thrive here.