Relativity Space
Space
StaffGPUSystemsEngineer
“Staff GPU Systems Engineer at Relativity Space. Skills: GPU Systems Engineering, AI/ML Inference, Performance Optimization, Linux Systems Administration. Own GPU compute environment. Setup driver integration”
What You'll Achieve.
Enable onboard AI/ML inference; Enable SAR reprocessing; Squeeze maximum science return; Sustain 10 Gbps data movement; Ensure platform reliably runs ML frameworks
Industry & Context.
Solving problems that haven’t been solved before; Diagnosed I/O bottlenecks; Tuned memory management; Understood workload throughput issues; GPU fault detection; Automated recovery
What They're Looking For.
Must Have
BS/MS in Computer Science or Electrical Engineering, 5+ years of relevant experience, Hands-on experience with GPU programming and compute frameworks, Linux systems administration and performance tuning skills, Experience with container technologies, HPC job scheduling concepts, Working proficiency in Python, C/C++ skills
Nice to Have
Experience with HPC cluster administration, ML infrastructure experience, Cloud GPU compute platforms at scale experience, Deep familiarity with ML framework runtime requirements, Knowledge of GPU compute architectures at the hardware level, Experience with high-throughput data movement and storage I/O optimization, Background in power-managed computing, Experience designing checkpoint/restart or fault-tolerant batch processing systems
What You'll Do.
Own GPU compute environment
Setup driver integration
Manage container runtime
Optimize compute performance
Build power/thermal-aware scheduling
Develop compute health monitoring
Integrate GPU drivers
Maintain SAR processing pipelines
How You'll Work.
Team & Collaboration
Collaborate across teams; Coordinate with storage platform; Coordinate with Platform RE; Work with operations team
Applying for this Staff GPU Systems Engineer role?
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