Senior GPU System Architect
$184k - $357k • US, CA, Santa Clara
Posted 1d ago
About the job
NVIDIA is seeking a GPU System Architect to design multi-GPU scale-up and scale-out systems for next-generation AI and HPC datacenter platforms. This role involves defining system architectures that integrate GPU compute, high-bandwidth memory, and interconnects to achieve industry-leading AI performance, scalability, and resilience. The ideal candidate will possess extensive experience in system-level fabric/networking architecture and hardware-software co-design.
Responsibilities
- Architect multi-GPU system topologies for scale-up and scale-out configurations, balancing AI throughput, scalability, and resilience.
- Define, modify, and evaluate future architectures for high-speed interconnects like NVLink and Ethernet, co-designed with the GPU memory system.
- Collaborate with teams to architect RDMA-capable hardware and define transport layer optimizations for large-scale GPU AI workload deployments.
- Utilize and modify system models, perform simulations, and conduct bottleneck analyses to guide design trade-offs.
- Work with GPU ASIC, compiler, library, and software stack teams to enable efficient hardware-software co-design across compute, memory, and communication layers.
- Contribute to interposer, package, PCB, and switch co-design for novel high-density multi-die, multi-package, multi-node rack-scale systems.
Requirements
- BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent experience.
- 8+ years of relevant experience in system design and/or ASIC/SoC architecture for GPU, CPU, or networking products.
- Deep understanding of communication interconnect protocols (NVLink, Ethernet, InfiniBand, CXL, PCIe).
- Experience with RDMA/RoCE or InfiniBand transport offload architectures.
- Proven ability to architect multi-GPU/multi-CPU topologies, considering bandwidth scaling, NUMA, memory models, coherency, and resilience.
- Experience with hardware-software interaction, drivers, runtimes, and performance tuning for distributed computing systems.
- Strong analytical and system modeling skills (Python, SystemC, or similar).
- Excellent cross-functional collaboration skills with silicon, packaging, board, and software teams.
Benefits
- Equity
- Benefits