Job description

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. We’re looking for a Production Test Lead to build the software foundation for manufacturing Physical Intelligence’s robotic systems at increasing volume. You’ll own the systems that technicians use to flash firmware, provision devices, configure hardware, execute calibration and test procedures, and record manufacturing results. You’ll translate evolving engineering processes into safe, guided workflows that can be executed consistently without requiring technicians to use a command line or understand the underlying implementation. This role sits at the intersection of runtime software, hardware engineering, manufacturing, test, infrastructure, and inventory systems. You will work closely with those teams to turn prototype scripts and manual procedures into secure, observable, versioned production tooling. 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. - 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. What we hope you'll bring - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field, or equivalent practical experience. - 5+ years of software engineering experience, preferably involving manufacturing, robotics, hardware test, embedded systems, or fleet operations. - Strong Python experience and familiarity with Linux systems, services, permissions, packaging, and process management. - Experience building reliable web applications and APIs used to orchestrate local or remote hardware. - Experience designing stateful workflows with retries, timeouts, resumability, cancellation, and failure recovery. - Familiarity with device provisioning, firmware flashing, OTA updates, calibration, or automated hardware testing. - Experience integrating with inventory, traceability, MES, ERP, or similar production systems. - Strong understanding of asynchronous jobs, idempotency, durable state, and distributed-system failure modes. - Experience with secure artifact distribution, authentication, authorization, and least-privilege hardware access. - Ability to diagnose issues across browsers, networks, operating systems, backend services, and physical devices. - Strong product judgment for technician-facing workflows and operational tooling. - Excellent cross-functional communication and project-management skills. Bonus points if you have - Experience with robotics, computer vision, camera calibration, networking hardware, Raspberry Pi-class devices, Bazel, Kubernetes, or cloud infrastructure. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Requirements

Must-haves

We’re looking for a Production Test Lead to build the software foundation for manufacturing Physical Intelligence’s robotic systems at increasing volume.
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.
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.
What we hope you'll bring
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field, or equivalent practical experience.
5+ years of software engineering experience, preferably involving manufacturing, robotics, hardware test, embedded systems, or fleet operations.
Strong Python experience and familiarity with Linux systems, services, permissions, packaging, and process management.
Experience building reliable web applications and APIs used to orchestrate local or remote hardware.
Experience designing stateful workflows with retries, timeouts, resumability, cancellation, and failure recovery.
Familiarity with device provisioning, firmware flashing, OTA updates, calibration, or automated hardware testing.
Experience integrating with inventory, traceability, MES, ERP, or similar production systems.
Strong understanding of asynchronous jobs, idempotency, durable state, and distributed-system failure modes.
Experience with secure artifact distribution, authentication, authorization, and least-privilege hardware access.
Ability to diagnose issues across browsers, networks, operating systems, backend services, and physical devices.

Nice-to-haves

Bonus points if you have

Application prep

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Keywords to mirror

aipythonkubernetes

Platform: ashby
Effort: quick

Benefits

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