Member of Technical Staff, Foundation Models

Role Description

• 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.

Qualifications

• 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.

Requirements

• Bonus: Experience with Vision-Language-Action models for robotics or web agents, embodied perception, or video generation.