Senior GPU System Architect

Overview

• NVIDIA has continuously reinvented itself.
• Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing.
• Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.NVIDIA has continuously reinvented itself.
• Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing.
• Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.
• We are seeking a GPU System Architect who will architect and design multi-GPU scale-up and scale-out systems for next-generation datacenter platforms for AI and HPC.
• The architect in this role will explore and define system architectures that tightly couple GPU compute, high-bandwidth memory, in-package interconnects and GPU-to-GPU communication fabric subsystems to deliver industry-leading AI performance, scalability and resilience.
• The ideal candidate combines deep hands-on system-level fabric/networking architecture experience, and practical hardware-software co-design expertise.
• What you will be doing: 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.
• What we need to see: BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent area.
• 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.
• Ways to stand out from the crowd: Background in system design for AI and HPC.
• Experience with NICs or DPU architecture and other transport offload engines.
• Expertise in chiplet interconnect architectures or multi-node fabrics and protocols for distributed computing.
• Hands-on experience with interposer or 2.5D/3D package co-design.