Software Engineer, High Performance Computing

About this role

SpaceX seeks a Software Engineer for their Starshield program to develop high-performance, reliable software systems controlling satellite constellations in low Earth orbit. You'll work across the full software lifecycle—from design through on-orbit deployment—collaborating with interdisciplinary teams to build secure, autonomous systems for government national security applications.

What you'll do

• Design and develop high-reliability C++ software systems for satellite constellation control and management
• Implement networking technologies to direct data across satellites, ground operations, and end users
• Write Linux-based C++ code for diverse processors (ARM, PowerPC, x86, etc.)
• Build automated ground software for data processing, command, and satellite control
• Develop models, simulations, and testing tools spanning virtualized, hardware-in-the-loop, and vehicle-in-the-loop environments
• Create continuous integration and deployment systems to enable frequent, reliable software updates

What they're looking for

• C++ programming for high-performance systems
• Linux kernel and systems development
• Computer architecture and networking fundamentals
• Debugging and performance optimization
• Networking protocols (TCP, UDP, etc.)
• Unit testing and test automation
• Ability to obtain Top Secret/SCI security clearance
• Image processing or machine learning (preferred)

Benefits

• Work on cutting-edge aerospace technology with direct mission impact
• Full software lifecycle ownership from concept to on-orbit operations
• Collaborate with interdisciplinary teams on next-generation space capabilities
• Access to real-world deployment and testing at scale
• Exposure to emerging technologies like inter-satellite lasers and space-based computing
• Location in Hawthorne, CA near SpaceX headquarters

Likely interview questions

• Tell us about a C++ project you developed that was deployed in a real-world production environment—what challenges did you face?
• How have you approached debugging and optimizing performance-critical systems in the past?