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.
Deploying robots into the real world takes more than a capable model - it takes designing a physical system that's fast, safe, and reliable enough to run unattended on a customer's floor, backed by software you can observe, debug, and trust if something goes wrong.
As a Robotics Software Engineer, you'll build that system. You'll integrate state-of-the-art models with robots that work on-site - building system safeguards, the teleoperation interfaces operators rely on, and the latency optimizations that make remote control feel instant. You'll work with researchers, platform engineers, and robot operators to make the whole stack dependable enough that customers bet their operations on it.
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
- Design remote teleoperation interfaces: Develop comfortable and precise interfaces for controlling robots with many degrees of freedom
- Optimize for low-latency network performance: Engineer teleoperation interfaces that can continue functioning even in weak internet areas
- Optimize System Performance: Profile and optimize across compute, I/O, memory, scheduling, networking, and storage to meet real-time constraints and increase throughput.
- Streaming & Video Systems: Develop and optimize real-time video streaming systems where frame timing and packet scheduling matter.
- Reliability & Debugging: Build tooling for profiling, tracing, and debugging timing issues across distributed systems and hardware interfaces.
- Cross-Functional Collaboration: Work with researchers, hardware engineers, and operations teams to integrate optimized pipelines into production workflows.
What We Hope You’ll Bring
- Strong programming skills in C++, Rust, or Python, with experience building and optimizing production software.
- Background in real-time or near–real-time systems, VR/AR, video pipelines, 3D engines, or streaming systems where latency budgets are strict.
- Ability to optimize across the entire stack - drivers, networking, compute workloads, video frameworks, and distributed components.
- Experience with profiling tools (perf, tracing, eBPF, GPU profilers, network analyzers) and comfort diving into complex performance issues.
- A mindset oriented around determinism, throughput, frame budgets, jitter minimization, and real-time correctness.
- Ability to collaborate deeply with robot users, researchers, and platform engineers to build a precise and comfortable teleoperation interface.
Bonus Points If You Have
- Experience with robot teleoperation systems, VR/AR platforms, or low-latency 3D engines.
- Camera system expertise (synchronization, capture pipelines, codecs, GPU offload).
- Streaming/video conferencing stack experience (WebRTC, real-time transport optimizations).
- Background in robotics or autonomous systems (implementation, not research).
- Familiarity with distributed systems that process real-time data flows.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
