GPU Architect

NVIDIA is hiring a GPU Architect in Bengaluru, India. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include Nvlink, Ethernet and Infinitband.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Architect high-performance multi-GPU scale-up and scale-out systems and interconnects for next-generation AI datacenters.

NvlinkEthernetInfinitbandCxlPcie

gpu-architectureasic-designhardware-software-co-designdatacenter-systems

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

How we rate this

GPU Architect at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

GPU Architect is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in India, Bengaluru.
The job was posted on September 5, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

GPU ArchitectureAsic DesignHardware Software Co DesignDatacenter SystemsNvlinkEthernetInfinitbandCxl

Questions you could be asked

Tell me about a project where gpu architecture was part of your work. What did you do?
Tell me about a project where asic design was part of your work. What did you do?
Tell me about a project where hardware software co design was part of your work. What did you do?
Tell me about a project where datacenter systems was part of your work. What did you do?
Walk me through how you've used Nvlink in your day-to-day work.

Adapt your resume

List these exact terms on your resume: GPU Architecture, Asic Design, Hardware Software Co Design, Datacenter Systems, and Nvlink. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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