Applied Researcher

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 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.

- 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

- 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

- 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.