Design, develop, and maintain system-level software to enable high-performance GPU-to-GPU communication.
Collaborate closely with cross-functional teams including hardware, firmware, system software to build and deliver next-generation GPU 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.
What we need to see:
B.S/M. S/ Ph.D. in computer science or a related field with 5+ years of relevant experience.
Excellent C/C++ programming and debugging skills, with some familiarity with Python.
Experience writing software applications that interface with device drivers and expose associated hardware functionality.
Solid understanding of computer systemarchitecture, operatingsystem and kernel internals.
Experience with Linux development; familiarity with Windows is a plus.
Background in multi-core / multi-process / multi-threaded programming environment.
Strong understanding of networking fundamentals and high-performance interconnection (e.g., InfiniBand, Ethernet)
Familiarity with OS virtualization technologies like KVM/QEMU/Hyper-V, etc.
Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Ways to stand out from the crowd:
Understanding of CUDA programming model and NVIDIA GPUs.
Knowledge of memory coherence and consistency models.
Familiarity with static and dynamic code analysis, fuzzing, negative testing, and other techniques.