Senior GPU Systems Architect: Multi-GPU AI Data Center

NVIDIA Corporation; Hinoba-an; Hybrid; PHP 7,524,000 - 11,912,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

NVIDIA invites a GPU System/Fabrics Architect to design scale-up and scale-out multi-GPU systems for cutting-edge AI datacenter workloads. You will drive architectures that tightly couple GPUs with memory, in-package interconnects, and GPU-to-GPU fabric transport to deliver top-tier performance, scalability, and resilience.

Join a collaborative, cross-functional team and define architectures for NVLink, Ethernet, and RDMA-enabled networks, shaping future AI acceleration platforms.

Qualifications

• BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent area.
• 8+ years 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.

Responsibilities

• 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.

Skills

System design

ASIC/SoC architecture

Interconnects

Performance modeling

Education

BS/MS/PhD in EE or CE

Job description

NVIDIA invites a GPU System/Fabrics Architect to design scale-up and scale-out multi-GPU systems for cutting-edge AI datacenter workloads. You will drive architectures that tightly couple GPUs with memory, in-package interconnects, and GPU-to-GPU fabric transport to deliver top-tier performance, scalability, and resilience.

Join a collaborative, cross-functional team and define architectures for NVLink, Ethernet, and RDMA-enabled networks, shaping future AI acceleration platforms.