Own GPU compute environment: setup, driver integration, containers, scheduling.
Profile and optimize compute: GPU utilization, memory bandwidth, I/O, storage.
Build power/thermal-aware compute scheduling around orbital constraints.
Develop compute health monitoring and automated recovery for GPUs.
Integrate GPU drivers with the payload Linux image; manage container runtime; ML/SAR pipelines.

🎯 Requirements

BS/MS in CS or EE; 5+ years relevant experience.
Hands-on GPU programming: CUDA, ROCm, or OpenCL with profiling.
Strong Linux administration; tune I/O, memory, throughput.
Experience with Docker/Podman and HPC scheduling concepts.
Python for tooling; C/C++ for performance-critical components.
Nice-to-have: HPC cluster, ML infra, or cloud GPU compute.

🎁 Benefits

Competitive salary and equity.
Generous PTO and sick leave.
Parental leave.
Annual learning and development stipend.
More benefits on our site.

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