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GPU Software Specialist, Onboard Compute

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GPU Software Specialist, Onboard Compute in USA

  • Muon Space
  • Full time
  • Email
  • San Jose, CA

Responsibilities

  • Design and implement GPU compute kernels for onboard image processing, radio signal processing, and ML inference.
  • Architect GPU pipelines that process live optical and radio sensor data and pass results to downlink or CPU decision-making subsystems.
  • Port, adapt, and optimize customer code, models, and algorithms for real-time, power-constrained on-orbit execution.
  • Profile and optimize GPU workloads, including occupancy, kernel launch configuration, and memory access patterns.
  • Own unit, system-level, and hardware-in-the-loop verification and validation of GPU software.
  • Define and operate the GPU build and CI/CD environment, including embedded-target cross-compilation toolchains and containerized builds.
  • Collaborate with flight software, FPGA, payload, and hardware engineers on interfaces, data formats, and timing budgets.
  • Translate mission and payload requirements into documented designs, trade studies, and interface specifications.
  • Work with internal and external customers to guide algorithm and model adaptation for embedded GPU hardware.

Requirements

  • Bachelor's or master's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Math, or a related technical field.
  • At least three years of professional experience developing GPU-accelerated software.
  • Strong proficiency in C/C++ or Rust and Python, including memory management, concurrency, and performance-oriented programming.
  • Production experience shipping GPU-accelerated software with CUDA, OpenCL, HIP, or similar technologies.
  • Deep knowledge of GPU architecture, SIMT execution, memory hierarchies, access patterns, occupancy, and kernel launch overhead.
  • Experience developing and debugging on embedded Linux, including cross-compilation, device tree basics, and userspace/kernel driver interaction.
  • Ability to write Linux userspace software integrating GPU compute through shared memory or similar mechanisms.
  • Ability to work with customers to adapt algorithms and models for efficient execution on embedded GPU hardware.
  • Strong written and verbal communication skills and ability to produce design documents, interface descriptions, and test reports.
  • Ability and willingness to obtain and maintain a U.S. security clearance; active clearance is a plus.
  • Experience with raw image or radio signal processing on GPUs is preferred.
  • Experience deploying ML inference on GPUs, including quantization and edge model optimization, is preferred.
  • Experience with DSP/RF workloads, Ethernet-based payload streams, RDMA, and zero-copy buffer techniques is preferred.
  • Experience with embedded software CI/CD, containerization, and hardware-in-the-loop test automation is preferred.
  • Space, aerospace, mission-critical software, customer-facing, or applied-engineering experience is preferred.

Benefits

  • Hybrid work arrangement with three days per week on-site in the San Jose, California office.
  • Medical, dental, and vision insurance.
  • 401(k) retirement plan.
  • Short- and long-term disability and life insurance.
  • Three weeks of paid vacation for new employees.
  • 12 paid holidays, unlimited sick time, and paid parental leave.
  • Equity compensation is provided in addition to salary.

Salary: $156k - $186k/yr

Muon Space

Muon Space is a comprehensive Space Systems Provider, specializing in the design, construction, and operation of Low Earth Orbit (LEO) satellite constellations that deliver essential data for various applications. Tailored for clients needing reliable Earth intelligence—from climate monitoring to...

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