Own and improve the end-to-end path for deploying Warp-based robotics and simulation components onto embedded platforms such as Jetson.
Build and maintain reproducible deployment workflows including cross-compilation, CI, packaging, and containerized delivery for embedded robotics targets.
Optimize on-device performance under real constraints including latency, throughput, memory footprint, thermals, and power.
Debug complex issues across the stack spanning Python, C++, CUDA, drivers, and embedded Linux, including hard-to-reproduce device-specific failures.
Integrate Warp components into robotics applications and frameworks, including ROS 2 and Isaac-based stacks, and work with partner teams to unblock adoption.
Develop system-level testing, validation, and performance regression infrastructure for embedded targets.
Collaborate with compiler, runtime, and kernel engineers to improve portability and performance across GPU architectures and embedded configurations.
Requirements
B.Sc. or M.Sc. or Ph.D. or equivalent experience in Computer Science, Computer Engineering, Robotics, Applied Math, Physics, or a related field
8+ years of experience with software engineering skills in C++ and Python, comfortable working across build systems and deployment tooling
Experience shipping software to embedded or edge devices, ideally in robotics, autonomy, or real-time systems.
Practical understanding of Linux-based deployment workflows including packaging, dependencies, drivers, and debugging in constrained environments.
Ability to reason about GPU performance and memory behavior, and to diagnose bottlenecks using profiling and system tools.
Strong collaboration and communication skills, with a bias toward execution and unblocking users.