Member of Technical Staff, Foundation Models (Bay Area)

 Posted a month ago
     
5-10 years experience
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AI Summary

Build end-to-end machine learning models for robotics control, including data curation, architecture design, and rigorous experimentation. Collaborate with robotics teams to develop internet-scale datasets and generative simulation techniques for Physical AI.

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

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