Robot Learning Research Engineer - Cross-Embodiment

Bonfirevc; Palo Alto (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Orbifold AI in Palo Alto, CA is seeking a Research Engineer in Robot Learning to advance data-driven manipulation for real hardware. You will own data strategies from human demonstration to trained policies and collaborate with partner teams on cross-embodiment transfer.

This role requires PhD or equivalent in robot learning, with first-author publications or shipped work, deep experience in imitation learning, PyTorch, and scalable workflows on Ray.

Qualifications

• PhD or equivalent research experience in robot learning, imitation learning, reinforcement learning, or a closely related field, with first-author publications or shipped work.
• You have trained manipulation policies that ran on real hardware, and you have debugged the gap between a good validation loss and a robot that still drops the object.
• Depth in imitation learning and VLA architectures, and real familiarity with the human-to-robot transfer literature.
• Strong PyTorch, comfortable at scale on Ray, and able to reason about how data quality, mixture and structure impact model performance.

Responsibilities

• Own cross-embodiment transfer: retargeting captured human motion onto robot kinematics, action-space design, and the correctness of the mapping at the moments that matter.
• Train manipulation policies on our data to establish what it is worth, reference implementations that demonstrate, rather than assert, that a dataset moves a partner’s metric.
• Run scaling studies on data mixture, quality and volume: how much human demonstration is worth how much teleoperation, and where the curve bends.
• Turn model behavior into data requirements. Where a policy fails for reasons rooted in the data rather than the architecture, say so precisely and specify the fix.
• Define how our data should be structured for training, formats, conventions, action representations, so it drops into a partner’s stack without a week of integration.
• Work directly with partner research teams on their training recipes, and bring back what you learn.

Skills

PyTorch

Ray

Imitation learning

Reinforcement learning

Education

PhD or equivalent

Tools

PyTorch

Ray

Job description

Orbifold AI in Palo Alto, CA is seeking a Research Engineer in Robot Learning to advance data-driven manipulation for real hardware. You will own data strategies from human demonstration to trained policies and collaborate with partner teams on cross-embodiment transfer.

This role requires PhD or equivalent in robot learning, with first-author publications or shipped work, deep experience in imitation learning, PyTorch, and scalable workflows on Ray.