Senior Software Architect, GPU Networking

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. The GPU Networking Software Architecture team is looking for a Senior Software Architect to help shape software for next-generation AI infrastructure. In this role, you will combine hands-on software architecture and development with system-level thinking. You will collaborate with experienced architects and engineering teams across NVIDIA while expanding your software architecture skills. Join us to help build the technologies that connect and manage large-scale accelerated computing systems.

What You’ll Be Doing

• Contribute to the architecture and prototyping of GPU networking software for large-scale AI infrastructure.
• Analyze requirements, evaluate design alternatives, and document technical decisions and trade-offs.
• Develop proofs of concept to evaluate interfaces, performance, resiliency, and software-hardware interactions.
• Collaborate with GPU, switch, firmware, driver, networking software, product, and architecture teams to move concepts toward implementation.
• Build knowledge of the GPU networking software stack and take increasing ownership of well-defined architectural areas.
  
  

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent experience.
• 5+ years of relevant software development experience in Linux environments.
• Strong understanding of software engineering fundamentals, including debugging, testing, data structures, concurrency, and operating-system concepts.
• Solid foundational knowledge of computer networking.
• Ability to understand complex systems, reason about component interfaces and design trade-offs, and communicate technical ideas clearly.
• Curiosity, initiative, collaborative problem-solving skills, and an eagerness to learn from experienced architects and engineers.
• Ability to work effectively with teams across locations and time zones.
  
  

• Knowledge in one or more of the following: Ethernet and IP datacenter protocols, management and telemetry protocols, GPU interconnects, Linux kernel or driver development, and network operating systems.
• Experience building prototypes or contributing to system-level architecture and design documents.
• Familiarity with AI communication libraries or programming models such as NCCL, UCX, MPI, CUDA, or equivalents.
• Knowledge of Kubernetes, containers, or cloud-native infrastructure.
• Experience analyzing performance, reliability, resiliency, or observability in complex software systems.