NVIDIA

1 month ago

GPU System Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Architect multi-GPU scale-up and scale-out datacenter systems for AI and HPC, defining high-speed interconnects (NVLink, Ethernet) and GPU-to-GPU communication fabric. Lead hardware-software co-design with ASIC, compiler and software teams; use system models and simulations to guide trade-offs, delivering scalable, resilient AI performance in hybrid work environments in Bengaluru, India.

Location: Bengaluru

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•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.

Key Requirements

•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 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:2+ yearsAIHPCDatacenterGPU

Education:Master's in Electrical Engineering

Skills:Cross-functional collaborationAnalytical thinkingProblem-solvingCommunicationTeamwork

Tech Stack:PythonSystemCNVLinkEthernetInfiniBandPCIeRDMARoCE

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 month ago

GPU System Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Bengaluru

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•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.

Key Requirements

•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 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:2+ yearsAIHPCDatacenterGPU

Education:Master's in Electrical Engineering

Skills:Cross-functional collaborationAnalytical thinkingProblem-solvingCommunicationTeamwork

Tech Stack:PythonSystemCNVLinkEthernetInfiniBandPCIeRDMARoCE

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor