Foundation Models

Genesis

  • San Carlos, California
  • 3 days ago

    Highlights

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

    Numbers & Facts

    LocationSan Carlos, California

    Description

    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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