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Senior GPU System Architect

NVIDIA· Architect
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Santa Clara, CA$184k - $356.5kfull-timePosted 5mo ago

About the role

Senior GPU System Architect responsible for designing multi-GPU scale-up and scale-out systems for AI and HPC datacenter platforms, coordinating hardware-software co-design across compute, memory, and interconnect subsystems, and driving system-level architecture decisions.

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 such as NVLink and Ethernet co-designed with the GPU memory system.
  • Collaborate with other teams to architect RDMA-capable hardware and define transport layer optimizations for GPU-based large scale AI workload deployments.
  • Use and modify system models, perform simulations and 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 consisting of hundreds of GPUs.

Qualifications

  • BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent experience.
  • 8 years or more of relevant experience in system design and/or ASIC/SoC architecture for GPU, CPU or networking products.
  • Deep understanding of communication interconnect protocols such as NVLink, Ethernet, InfiniBand, CXL and PCIe.
  • Experience with RDMA/RoCE or InfiniBand transport offload architectures.
  • Proven ability to architect multi-GPU/multi-CPU topologies, with awareness of bandwidth scaling, NUMA, memory models, coherency and resilience.
  • Experience with hardware-software interaction, drivers and runtimes, and performance tuning for modern 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.

Skills

Required:System design of multi-GPU topologiesInterconnect protocols (NVLink, Ethernet, InfiniBand, CXL, PCIe)RDMA/offload architecturesHardware-software co-design

Benefits

  • You will also be eligible for equity and benefits.
Last updated Jul 3, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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