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Deployments Software Engineer

Physical Intelligence · San Francisco, United States

External listingfull-timeabout 2 months ago

About The Role

Join our Deployments team as a Software Engineer, where you'll tackle real-world problems with our models and robots. You'll work on integrating with customer workflows, training models, and ensuring on-site reliability. Your responsibilities will include designing remote teleoperation interfaces, optimizing system performance, developing real-time video streaming systems, and collaborating with cross-functional teams. Ideal candidates will have a background in real-time systems, strong programming skills, and experience with robot teleoperation systems or low-latency 3D engines.

  • Design and develop remote teleoperation interfaces for controlling robots with many degrees of freedom, ensuring comfort and precision.
  • Optimize system performance across compute, I/O, memory, scheduling, networking, and storage to meet real-time constraints and increase throughput.
  • Collaborate with researchers, hardware engineers, and operations teams to integrate optimized pipelines into production workflows, ensuring reliability and debugging.
  • 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 collaborate deeply with robot users, researchers, and platform engineers to build a precise and comfortable teleoperation interface
  • Experience with profiling tools (perf, tracing, eBPF, GPU profilers, network analyzers) and comfort diving into complex performance issues
  • Ability to optimize across the entire stack - drivers, networking, compute workloads, video frameworks, and distributed components
  • A mindset oriented around determinism, throughput, frame budgets, jitter minimization, and real-time correctness
  • Strong programming skills in C++, Rust, or Python, with experience building and optimizing production software
  • 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)
  • Familiarity with distributed systems that process real-time data flows
  • Background in robotics or autonomous systems (implementation, not research)

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