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San Francisco, California, United States
Onsite
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 AI
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