GPU Architect

NVIDIA Gruppe; Bengaluru; Hybrid; INR 3,000,000 - 4,200,000; Full time

Job summary

NVIDIA is seeking a GPU System/Fabrics Architect to design multi-GPU scale-up and scale-out AI datacenter platforms. The architect will explore architectures that tightly couple GPU compute, high-bandwidth memory, in-package interconnects, and GPU-to-GPU fabric transport to deliver industry-leading AI performance and resilience.

You will work with GPU ASIC, compiler, library, and software teams to enable efficient hardware-software co-design across compute, memory, and communication layers.

Qualifications

• BS/MS/PhD in Electrical or Computer Engineering or equivalent.
• 2+ years in system design or ASIC/SoC architecture for GPU/CPU/XPU or networking.
• Deep understanding of Ethernet, InfiniBand, NVLink, CXL, PCIe interconnects.
• Proven ability to architect multi-GPU/multi-CPU topologies with bandwidth scaling, NUMA, memory coherency.
• Strong analytical and system modeling for performance, power, resilience.
• Excellent cross-functional collaboration and teamwork.

Responsibilities

• Architect multi-GPU systems for scale-up and scale-out configurations focusing on AI performance and resilience.
• Define and evaluate future architectures for high-speed interconnects with GPU memory and networking hardware.
• Architect RDMA-capable hardware and optimize transport for large-scale AI workloads.
• Explore high-density multi-chiplet, multi-package, multi-node AI systems.
• Use models, simulations, and bottleneck analyses to guide design trade-offs.
• Collaborate with GPU ASIC, compiler, library, and software teams for co-design across compute, memory, and communication.

Skills

System design

ASIC/SoC architecture

Interconnect protocols

Multi-GPU topologies

Performance modeling

Collaboration

Education

BS/MS/PhD in Electrical/Computer Engineering

Job description

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.

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.

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