Senior AI Systems Architect — GPU Interconnects + Equity

NVIDIA Corporation; Santa Clara (CA); On-site; USD 224,000 - 431,000; Full time

Job summary

NVIDIA California is seeking a Senior Architect to own core modules of distributed AI networking software. You will drive end-to-end ownership from research questions to shipping production code, working at the boundary of applied research and production engineering.

You will architect high-performance communication libraries, drive hardware-software co-optimization with GPU/DPU/NIC teams, and mentor engineers while contributing to open-source projects. Competitive compensation offered.

Qualifications

• 12+ years in systems software and/or networking with ownership of complex projects.
• MS, PhD or equivalent in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Strong C/C++/Rust systems programming with comfort in performance profiling and low-level debugging.
• Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns.

Responsibilities

• Architect high-performance communication and memory management libraries for distributed AI.
• Drive hardware-software co-optimization with GPU, DPU, NIC, and switch teams through GPUDirect RDMA, NVLink, and next-generation interconnects.
• Profiling and optimizing data movement across GPU memory, system DRAM, NVMe, and network fabrics.
• Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM.
• Contributing to and maintaining open-source projects, mentoring engineers, conducting design reviews, and prototyping experimental technologies to evaluate their viability.

Skills

C/C++

Rust

Performance profiling

Transformer architectures

Distributed training

Model parallelism

Education

MS or PhD in CS/CE/EE

Tools

InfiniBand

RoCE

RDMA

NVLink

GPUDirect

vLLM

TensorRT-LLM

Job description

NVIDIA California is seeking a Senior Architect to own core modules of distributed AI networking software. You will drive end-to-end ownership from research questions to shipping production code, working at the boundary of applied research and production engineering.

You will architect high-performance communication libraries, drive hardware-software co-optimization with GPU/DPU/NIC teams, and mentor engineers while contributing to open-source projects. Competitive compensation offered.