Foundation Models — San Francisco, CA

What You'll Do

• Build machine learning models for robotics control end-to-end: data curation, careful evaluation, model architecture, training/inference stacks, rigorous experiments

• Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets

• Curate the world’s best Internet-scale datasets for embodied perception and first-person robot video generation

• Design new generative simulation techniques to expand simulation data scale and diversity, training and evaluating generative models of 3D objects and environments, and language/code models to generate tasks and reward functions

• Collaborate with a team of driven individuals committed to building general-purpose Physical gU

What You'll Bring

• Passion for your craft and demonstrated excellence in full-stack foundation model research and engineering

• Exceptional ownership and initiative—finding and solving problems independently

• Extensive experience pioneering new machine learning ideas or refining existing methods, supported by first-author publications or impactful projects (5+ years)

• A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail

• Production-level expertise in modern Python

• Bonus: Experience with Vision-Language-Action models for robotics or web agents, embodied perception, or video generation