Fullstack Software Engineer at Physical Intelligence (San Francisco, CA)
Physical Intelligence· San Francisco, CA·
Role details
Job description
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.
As a Fullstack Software Engineer, you will build internal products that help Pi's research and operations teams move faster. You will work closely with researchers, prototypers, operators, and other engineers to turn operational workflows into reliable software.
The Team
Fullstack builds the internal software the rest of Pi runs on. Our users span the path from research intent to physical execution: researchers designing experiments and requesting data, Research Ops working across feasibility, task design, environments, prototyping, and instructions, and Production Ops running data collection, evals, and deployments across our lab, warehouse, and real-world deployments.
Annotation sits at the front of that chain, determining what our models learn from the data we collect, and this is where this role will start.
In This Role You Will
- Own annotation tooling: Build the platform and workflows for annotation generation, from the interfaces annotators work in to the pipelines behind them, and translate requirements from researchers into an actionable plan and the software to execute it.
- Make annotation legible: Build the systems that track quality, cost, throughput, and coverage so researchers can see what they are getting and decide what to change.
- Own researcher request and planning workflows: Redesign how researchers and prototypers turn ambiguous research needs into executable work, and create the software layer for understanding capacity and making tradeoffs across competing priorities.
- Build research and ops-facing tooling: Dataset browsing, eval dashboards, and the throughput, quality, and progress tracking Production Ops needs across our lab, warehouse, and real-world sites.
- Act as your own PM: Gather requirements, prioritize work, define success metrics, write specs, ship tools, drive adoption, and iterate based on feedback.
- Ship production-quality software: Build reliable frontend interfaces, backend APIs, data models, dashboards, and cloud services. You should be comfortable shipping and supporting production-grade services.
What We Hope You'll Bring
- Strong full stack engineering experience building production web applications and APIs, especially with React, TypeScript, and Python.
- Experience with relational databases (we use Postgres), analytical systems (ClickHouse), and queueing systems.
- Familiarity with cloud and containerized environments such as GCP and Kubernetes.
- Comfort designing workflows where people, models, and software have to function as one system.
- Strong product judgment and attention to detail.
- Experience working directly with users, iterating from feedback, and navigating ambiguous workflows and evolving requirements.
- Ability to start with a practical v0 and build toward scalable, production-quality systems.
Bonus Points
- Former founder, early employee, or other demonstration of comfort with ambiguity and solving hard problems end to end.
- Experience building data labeling platforms, human-in-the-loop tools, or other data-centric AI systems.
- Experience building internal tools specifically for research, robotics, or operationally-intensive problems.
- Experience with tasking systems, instruction management, scheduling, resource allocation, or workflow orchestration.
- Experience with our specific stack: React, TypeScript, Python, Postgres, ClickHouse, GCP, and Kubernetes.
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.