Applied Researcher at Physical Intelligence (San Francisco, CA)
Physical Intelligence· San Francisco, CA·
Role details
Summary
Deploy and debug learned policies on physical robots while training and tuning models to improve real-world performance. Bridge research and operations by translating advances into deployable systems and collaborating with partners and operators.
Job description
Who We Are
Physical Intelligence is bringing general-purpose AI into the physical world. We are a group 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 The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we’re a full-stack robotics team - whether it’s thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will
- Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware).
- Train and tune policies, curate data, and iterate to improve real-world performance.
- Write production-quality code that interfaces with Pi’s infrastructure.
- Work with operators to set up tests, evals, and data collection pipelines.
- Engage with partners to understand use cases and observe robots in deployment contexts.
- Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers.
- Define and shape a vision for what real-world deployments will look like in the long-term
What We Hope You’ll Bring
- Hands-on experience deploying robots or autonomous systems in real-world environments
- Strong engineering skills: clean Python, ability to interface with infrastructure, debugging instincts
- Ability to debug the full stack from perception to control
- Practical mindset: motivated by making things work, not by open-ended research
- Clear communication with researchers, operators, and occasionally partners Bonus Points If You Have
- Founded or worked at an early-stage robotics or AV company
- PhD in relevant field
- Intuition for policy training, neural network debugging, and data curation
- Experience with robot manipulation platforms
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.