Feeny
Physical Intelligence

Embedded Engineer at Physical Intelligence (San Francisco, CA)

Physical Intelligence· San Francisco, CA·

Role details

Work type
Onsite
Employment
Full-Time

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. The team This role is part of the Runtime team, but will include deep collaboration with the Research, Hardware, and Fleet teams. In this role you will:

  • Drive the architecture and implementation of embedded firmware for devices crucial to PI’s data collection goals
  • Work with hardware and software teams to ensure the new devices we are building work seamlessly with existing and future data pipelines
  • Embedded Linux System Bring-up: Lead the integration of embedded Linux devices with real-time sensor processing. This includes developing drivers for high-speed sensors, BSP development and customization, kernel configuration and debugging, hardware bring-up, and performance tuning across the hardware/software boundary.
  • Hardware/Software Debugging: Use hardware abstraction tools and laboratory equipment to identify and resolve complex timing issues, race conditions, and hardware-software interface bugs.
  • Power Optimization: Analyze and reduce power consumption for battery-operated devices, including on radio sleep states and sensor low-power modes.

What we hope you'll bring:

  • BS/MS in Computer Science, Electrical Engineering, or related field.
  • Strong software engineering and infrastructure skills, including building data pipelines, evaluation frameworks, and tools for rapid iteration.
  • Comfort working hands-on with hardware.
  • Strong communication skills for collaborating with hardware, software, and research teams
  • Demonstrated experience leading initiatives from concept to production on aggressive schedules, and turning ambiguous product goals into functional requirements
  • Experience leading initial board bring-up and software design for first-of-their-kind embedded devices.
  • Hands-on experience with SPI, I2C, UART, USB, and the ability to debug complex hardware-software interactions.
  • Experience architecting, implementing and debugging concurrent and multithreaded firmware services
  • Deep understanding of modern operating systems, computer architecture, and trade-offs between compute, memory, and storage.
  • Experience bringing up and integrating sensors on embedded systems; camera system bring-up, integration, and tuning is a plus.
  • Proficiency in C++
  • Familiarity with Bash scripting and Python for tooling and automation.

Bonus points if you have:

  • Nice to have: Direct experience with Linux Kernel development, including writing or debugging drivers, managing device trees, or optimizing kernel-space performance.

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

Why work at Physical Intelligence

  • Culture: Described as a “pure company” – internally driven by research needs, not external market demands. Highly collaborative, with a mix of engineers, scientists, and roboticists working together.
  • Work Environment: Hybrid/in-office – most roles require on-site presence in San Francisco (396 Treat Ave), though some remote flexibility exists. In-office setting with a “no reception” vibe, open lab space with robot stations.
  • Growth: Team has scaled from ~80 (Jan 2026) to 163 (mid-2026) and is still hiring across research, ML infra, hardware, and engineering roles. Plans to grow “as slowly as possible” to maintain quality.
  • Perks & Engineering Highlights: Access to cutting-edge robotics hardware and compute resources; opportunity to publish research and open-source code; exposure to a wide variety of real-world automation challenges (e.g., robots learning to fold pants, peel vegetables, make espresso). Employees come from top institutions like Berkeley, Stanford, Google, NVIDIA, and Anduril.

Application questions