Physical Intelligence
Product Engineer
San Francisco · Staff+
Sponsorship not specifiedDetected 12 days ago
PythonReactFull-Stack DevelopmentPostgreSQLGCPKubernetesWebSocketsMachine LearningRoboticsResearchCommunication
About the role
- Member of Technical Staff - Product Engineering
- THE PRODUCT ENGINEERING TEAM BUILDS THE PLATFORM THAT LETS OTHER COMPANIES USE PI'S MODELS: ACCESS TO OUR MODELS AND THE SERVICES AROUND THEM, SO A ROBOTICS COMPANY CAN BUILD ON PI THE WAY DEVELOPERS BUILD ON API-BASED LLMS. SEE THE PHYSICAL INTELLIGENCE LAYER https://www.pi.website/blog/partner.
Responsibilities
- This spans data ingestion and APIs, a partner portal, and deployment integrations, all working end to end and self-serve.
- Ingest partner data end to end: take a new data or robot partner from their first sample to featurized, validated data in our system, and to a checkpoint they can eval.
- Be the engineer embedded in partner engagements: sit in the partner channel, debug their deployment across the full stack, unblock them, and translate what they need into what we build.
- Bridge research and partners: turn research advances into deployable systems, and surface real-world failure modes back to researchers and engineers.
- ACCESS TO OUR MODELS AND THE SERVICES AROUND THEM, SO A ROBOTICS COMPANY CAN BUILD ON PI THE WAY DEVELOPERS BUILD ON API-BASED LLMS.
- SEE THE PHYSICAL INTELLIGENCE LAYER https://www.pi.website/blog/partner.
- YOU TAKE A NEW PARTNER FROM RAW DATA TO A DEPLOYED, EVALUATED MODEL WITH LITTLE HAND-HOLDING.
Requirements
- This is a software and systems role first, so a robotics or ML research background is not required.
- We care more about what you can do than whether you fit a standard profile.
- A practical, ownership mindset: you are motivated by making things work end to end.
Skills
- clean Python, the ability to interface with infrastructure, and sharp debugging instincts.
- Clear communication with researchers, operators, and partners.
- Low-latency and real-time networking experience (inference transport, streaming, QUIC or websockets).
- Experience with robot manipulation platforms, VLAs, or other ML models.
- Familiarity with our stack: Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React and TypeScript.
Company info
- Founded or worked at an early-stage robotics, AV, or infrastructure startup.
Apply directly at Physical Intelligence →Create a free account for alerts like thisView Physical Intelligence immigration profile
This listing is sourced directly from Physical Intelligence's careers page and normalized into a canonical job model.