Production Test Engineer

Physical Intelligence is bringing general-purpose AI into the physical world. We are a team of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically actuated devices of the future.

The Team

This role is part of the team building PI’s manufacturing and hardware-test infrastructure. It will collaborate deeply with hardware engineering, runtime, embedded software, infrastructure, inventory, πBuild, and πFab.

In This Role You Will

• Own the architecture and development of PI’s manufacturing software platform.
• Build technician-friendly, step-by-step workflows for assembly, flashing, provisioning, calibration, and final test.
• Convert engineering scripts and manual procedures into versioned, repeatable manufacturing operations.
• Develop local station software that securely exposes allowlisted hardware capabilities to hosted manufacturing workflows.
• Design workflow primitives for automated steps, operator instructions, retries, timeouts, cancellation, resumability, and acceptance criteria.
• Build reliable mechanisms for downloading, caching, verifying, and updating firmware and manufacturing binaries.
• Integrate manufacturing workflows with inventory systems to register hardware, assign identities, and record required metadata.
• Establish traceability for operators, stations, devices, software versions, step results, durations, and captured test artifacts.
• Build observability that allows engineers to inspect production progress and diagnose failures remotely.
• Design systems that continue operating through temporary network failures and synchronize results when connectivity returns.
• Implement safe authentication, authorization, and privilege boundaries for software that controls local hardware.
• Develop automated tests for workflow behavior and hardware-independent failure handling.
• Debug problems across cloud services, local Linux stations, networks, embedded devices, and test equipment.
• Partner with manufacturing and hardware engineers to define acceptance criteria and automate quality checks.
• Define and track manufacturing-software KPIs such as station availability, workflow completion rate, first-pass yield, retry rate, and failure category.
• Establish technical standards that allow new manufacturing workflows and hardware products to share a common platform without becoming tightly coupled.
  
  

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.