Software Engineer, Robot Interfaces
Physical Intelligence
Summary
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.
Job description
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 operators, roboticists, researchers, and other engineers to turn physical 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 task design, environments, prototyping, and instructions, and Production Ops running collection, evals, and deployments across our lab, warehouse, and real-world sites.
In This Role You Will
- Own the human-robot interfaces: The software people use to run, monitor, and debug robots, from setup and calibration through live operation and review. Someone lives in this for an entire shift, and small friction compounds fast.
- Design for the whole shift, not just the episode: Time on a robot is a fraction of the day. The rest is preparation, troubleshooting, handoffs, and feedback, spread today across several tools and several people. The goal is not to expose every tool, but to build one surface that tells someone what deserves their attention now and notices when they're stuck.
- Design for safety: Make state unambiguous, make failure obvious, and make the safe action the easy one. Assume the network drops mid-episode or a camera dies, and design so the system degrades predictably rather than surprisingly.
- Own the realtime edge: Video, robot state, and control at latency budgets tight enough that teleoperation feels direct, plus the controllers, headsets, pedals, and sensors people drive with.
- Draw the line between device and cloud: Decide what has to stay local because it is safety-critical or latency-sensitive, and what belongs in a control plane that owns identity, state, and coordination across sites.
- Ship into the physical world: On-prem and on-device deployment, versioning and rollout across lab, warehouse, and partner sites, and enough observability to know what is running where.
- Make the work measurable: Instrument these interfaces well enough that we can see where the operation loses time, then test changes against it.
- Act as your own PM: Gather requirements, prioritize, define success metrics, ship, and drive adoption. That starts by standing in the room and watching a shift.
What We Hope You'll Bring
- Strong fullstack engineering experience building production web applications and APIs, especially with React, TypeScript, and Python.
- Realtime web experience: WebRTC, WebSockets, streaming video, state synchronization, and the debugging that comes with all of it.
- Comfort with binary wire formats and schema-defined interfaces: protobuf, gRPC, or similar. Most of what these interfaces talk to is not a REST API.
- Experience shipping software that runs on machines you do not administer: on-prem or on-device deployment, degraded-network operation, versioning across a fleet.
- Strong UX instincts for high-stakes, high-frequency interfaces, where the user is standing up, under time pressure, and a mistake has physical consequences.
- Comfort designing workflows where people, hardware, and software have to function as one system.
- Strong product judgment, and experience working directly with users through ambiguous workflows and evolving requirements.
Bonus Points
- Former founder, early employee, or other demonstration of comfort with ambiguity and solving hard problems end to end.
- Experience with teleoperation, robotics, or other robot-adjacent software.
- Experience with safety-critical or industrial systems (control room, medical device, aviation, automotive, or similar) where interface decisions carry real consequences.
- Hardware-adjacent background: firmware, embedded, device integration, or having shipped software alongside a physical product.
- Experience with workflow, dispatch, or scheduling systems that direct human work in the physical world.
- Experience with our specific stack: React, TypeScript, Python, Postgres, GCP, and Kubernetes.
Requirements
- Strong fullstack engineering experience building production web applications and APIs, especially with React, TypeScript, and Python.
- Realtime web experience: WebRTC, WebSockets, streaming video, state synchronization, and the debugging that comes with all of it.
- Comfort with binary wire formats and schema-defined interfaces: protobuf, gRPC, or similar.
- Experience shipping software that runs on machines you do not administer: on-prem or on-device deployment, degraded-network operation, versioning across a fleet.
- Strong UX instincts for high-stakes, high-frequency interfaces.
- Comfort designing workflows where people, hardware, and software have to function as one system.
- Strong product judgment, and experience working directly with users through ambiguous workflows and evolving requirements.
Company overview
Physical Intelligence is a pioneering company at the intersection of artificial intelligence and robotics, founded in 2024 with headquarters in San Francisco, California. The company specializes in developing general-purpose AI foundation models and learning algorithms designed to power robots and physically-actuated devices across multiple industries. Their core technology focuses on creating universal robotic intelligence through advanced Vision-Language-Action (VLA) systems that enable robots to understand visual inputs, process natural language commands, and execute appropriate physical actions in real-world environments. The company's flagship π-zero (pi-zero) model represents a significant advancement in cross-embodiment learning, allowing their AI systems to generalize across different robotic platforms and applications without requiring complete retraining. With substantial backing from top-tier investors including Jeff Bezos, Thrive Capital, OpenAI, and Sequoia Capital, Physical Intelligence has rapidly emerged as a leader in the physical AI space, achieving a $2.4 billion valuation. The company employs 51-200 professionals including engineers, scientists, roboticists, and company builders who are working to bring general-purpose AI into the physical world, fundamentally transforming how robots interact with and manipulate their environments.