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Design, develop, and maintain system-level software to support GPU-to-GPU communication.
Collaborate with cross-functional hardware and software teams to build next-generation networking solutions.
Contribute to scalable and reliable GPU fabric architecture for large compute clusters.
Align software development with customer needs and real-world deployment environments.
A degree or equivalent experience in Computer Science, Electrical Engineering, or a related field (B.S., M.S., or Ph.D.).
5+ years of professional software development experience.
Proficiency in C/C++, with strong debugging and system-level problem-solving skills.
Experience developing software that interacts with hardware and device drivers.
Solid understanding of system architecture, operating systems, and kernel internals.
Background in multi-threaded and distributed systems development.
Experience with Linux development; familiarity with Windows is a plus.
Strong understanding of networking fundamentals and high-performance interconnects (e.g., InfiniBand, Ethernet).
Familiarity with OS virtualization technologies like KVM, QEMU, or Hyper-V.
Comfortable collaborating with a distributed team across different time zones.
Experience with the CUDA programming model and NVIDIA GPU architecture.
Understanding of memory consistency and coherence models.
Exposure to static/dynamic code analysis, fuzz testing, or fault injection techniques.
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