Join NVIDIA, a pioneer in GPU technology, as a GPU System/Fabrics Architect. You will architect and design advanced multi-GPU systems for next-generation AI datacenter platforms. This role involves defining architectures that tightly integrate GPU compute, memory, and high-speed interconnects to achieve unparalleled AI performance, scalability, and resilience.

NVIDIA's invention of the GPU revolutionized computer graphics and parallel computing, and we continue to innovate at the forefront of AI research. We are seeking individuals passionate about pushing the boundaries of what's possible in AI computation.

Architect multi-GPU systems for scale-up and scale-out configurations, prioritizing AI performance, scalability, and resilience.

Define, modify, and evaluate architectures for high-speed interconnects like NVLink and Ethernet, co-designing with GPU memory and networking hardware.

Design RDMA-capable hardware and optimize transport layers for large-scale GPU-based AI workloads.

Explore and develop novel high-density multi-chiplet, multi-package, and rack-scale AI systems with extensive copper and optical interconnects.

Utilize and adapt system models, conduct simulations, and perform bottleneck analyses to inform design choices.

Collaborate with GPU ASIC, compiler, library, and software teams to ensure efficient hardware-software co-design across compute, memory, and communication layers.

A Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or a related field is required, along with 2+ years of experience in system design or ASIC/SoC architecture for GPU, CPU, XPU, or networking products.

Demonstrate a deep understanding of communication interconnect protocols such as Ethernet, InfiniBand, NVLink, CXL, and PCIe. Proven ability in architecting multi-GPU/multi-CPU topologies, with an awareness of bandwidth scaling, NUMA, memory models, coherency, and resilience.

Exhibit strong analytical and system modeling skills for performance, power, and resilience evaluation. Excellent cross-functional collaboration and communication skills are essential.