Foundation Models
AI Summary
Build machine learning models for robotics control end-to-end, curate large-scale datasets for embodied perception, design generative simulation techniques, and collaborate with robotics teams to train and evaluate foundation models.
About this role
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
Skills
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