Senior Software Engineer, Fabric Networking - GPU

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence.

We are looking for highly motivated Senior Software Engineers to work on our GPU NVLink Fabric Networking team. You’ll be part of a team responsible for defining the next generation communications standards and products building on our current NVLink and NVSwitch technology.

What You Will Be Doing

• 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.
  
  

• 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 system architecture, operating system 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.
  
  

• 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.