Lead Physical AI & Robotics Researcher

Feather Robotics; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Feather Robotics in San Francisco seeks a Physical AI Researcher to lead applied research advancing reliability and data efficiency for manipulation in general-purpose robots.

You will own the research stack, collaborate with engineers to integrate perception, control, and cognition, and push Physical AI toward mainstream commercial deployment through rigorous experiments and publications.

Qualifications

• MS or PhD in EECS, Robotics, CS, AI, or related field, or equivalent industry experience
• Strong background in machine learning, with applied work in robotics or embodied AI
• Experience with one or more of: Vision-Language Models (VLAs), imitation learning, diffusion policies, reinforcement learning, navigation
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
• Track record of impactful projects, whether in academia, open-source, or industry
• Publications in top robotics conferences (ICRA, CoRL, RSS, IROS, etc.)

Responsibilities

• Develop, train, and deploy machine learning models for general-purpose robots
• Implement and optimize algorithms in areas such as imitation learning, RL, diffusion policies, VLA, and navigation
• Collaborate with robotics engineers to integrate perception, control, and cognition into a unified system
• Conduct applied research that pushes Physical AI forward, with an emphasis on commercial viability
• Analyze performance, debug complex behaviors, and continuously improve model robustness in the real world

Skills

Machine learning

Robotics/Embodied AI

Python

PyTorch

Publications

Education

MS or PhD in EECS, Robotics, CS, AI, or related field

Tools

PyTorch

TensorFlow

Job description

Feather Robotics in San Francisco seeks a Physical AI Researcher to lead applied research advancing reliability and data efficiency for manipulation in general-purpose robots.

You will own the research stack, collaborate with engineers to integrate perception, control, and cognition, and push Physical AI toward mainstream commercial deployment through rigorous experiments and publications.