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At a glance
Job overview
The role involves building end-to-end machine learning models for robotics control, curating large-scale datasets, designing generative simulation techniques, and collaborating with simulation and real‑world robotics teams to advance physical AI.
Skills & qualifications
Skills
Qualifications
Full job description
What You'll Do
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Build machine learning models for robotics control end-to-end: data curation, careful evaluation, model architecture, training/inference stacks, rigorous experiments
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Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets
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Curate the world’s best Internet-scale datasets for embodied perception and first-person robot video generation
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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
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Collaborate with a team of driven individuals committed to building general-purpose Physical AI
What You'll Bring
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Passion for your craft and demonstrated excellence in full-stack foundation model research and engineering
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Exceptional ownership and initiative—finding and solving problems independently
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Extensive experience pioneering new machine learning ideas or refining existing methods, supported by first-author publications or impactful projects (5+ years)
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A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail
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Production-level expertise in modern Python
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Bonus: Experience with Vision-Language-Action models for robotics or web agents, embodied perception, or video generation
You've read the whole posting — now see how you match it.