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/Fabrics Architect who will architect and design multi-GPU scale-up and scale-out systems for next-generation AI datacenter platforms. The architect in this role will explore and define architectures that tightly couple GPU compute, high-bandwidth memory, in-package interconnects, and GPU-to-GPU communication Fabric transport/routing subsystems to deliver industry-leading AI performance, scalability, and resilience.
What you will be doing:
Architect multi-GPU systems for scale-up and scale-out configurations, balancing AI performance, scalability, and resilience for the Agentic era.
Define, modify, and evaluate future architectures for high-speed interconnects such as NVLink and Ethernet co-designed with the GPU memory system and networking hardware.
Architect RDMA-capable hardware and define transport layer optimizations for GPU-based large scale AI workload deployments.
Explore and build novel high-density multi-chiplet, multi-package, multi-node rack-scale AI systems consisting of hundreds/thousands of copper and optically interconnected GPUs.
Use and modify system models, perform simulations, and bottleneck analyses to guide design trade-offs.
Work with GPU ASIC, compiler, library, and software teams to enable efficient hardware-software co-design across compute, memory, and communication layers.
What we need to see:
BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent area.
2+ years or more of relevant experience in system design and/or ASIC/SoC architecture for GPU, CPU, XPU, or networking products.
Deep understanding of communication interconnect protocols such as Ethernet, InfiniBand, NVLink, CXL and PCIe.
Proven ability to architect multi-GPU/multi-CPU topologies, with awareness of bandwidth scaling, NUMA, memory models, coherency, and resilience.
Strong analytical and system modeling skills for performance, power, resilience.
Excellent cross-functional collaboration and skills.
Ways to stand out from the crowd:
Experience with NICs, DPUs, RDMA/RoCE or InfiniBand transport offload architectures.
Expertise in chiplet interconnect architectures or multi-node fabrics and protocols for high-performance distributed computing.
#LI-Hybrid
Skills Required
- BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent
- 2+ years experience in system design and/or ASIC/SoC architecture for GPU, CPU, or networking products
- Deep understanding of interconnect protocols (NVLink, Ethernet, InfiniBand, CXL, PCIe)
- Experience with RDMA/RoCE or InfiniBand transport offload architectures
- 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, runtimes, and performance tuning for distributed systems
- Strong analytical and system modeling skills (Python, SystemC, or similar)
- Excellent cross-functional collaboration with silicon, packaging, board, and software teams
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
