Member of Technical Staff - Human Modeling & Embodied Intelligence

We're an early-stage embodied AI company (backed by top-tier VCs) teaching robots to use their hands by learning from human. We turn egocentric and multi-view human video into precise 3D hand and body motion and use it to train robot policies. We operate robot arms, dexterous hands, and teleoperation rigs, and we train on large-scale GPU compute.

You’ll own our human modeling stack: the models and pipeline that turn raw human video into accurate 3D hand, hand–object, and whole-body motion. You’ll set the technical direction for this area and help build the team around it.

• Build and train models for egocentric 3D hand pose (MANO) and hand–object interaction from head-mounted, wrist, and multi-view cameras.
• Recover whole-body human motion (SMPL-X) in world coordinates from egocentric and third-person video.
• Turn research models into a pipeline that processes thousands of hours of video, with automatic QA and failure detection.
• Define accuracy specs and ground truth, and measure which tracking errors actually matter for robot learning.
• Work with robotics engineers on capture rigs, calibration, and retargeting human motion to robot hands and arms.

• Deep experience in 3D hand or human pose estimation, motion capture, or 4D human reconstruction, shown through top-venue papers, widely used code, or shipped systems.
• Fluency with MANO / SMPL-X, camera models, and multi-view geometry.
• Strong PyTorch skills and experience training large vision models, including distributed training.
• Rigor with real-world data: you validate data and baselines before spending GPU hours.
• PhD in CS, robotics, EE, or a related field, or equivalent research experience.

• Experience with egocentric devices or datasets (Project Aria, Quest; Ego-Exo4D, HOT3D, ARCTIC).
• Hand–object contact or grasping, robot learning from human video, or SLAM/VIO.

• Founding-team scope and equity
• Salary and health benefits
• Real robots and large-scale GPU compute