Principal Architect, AI Networking
NVIDIA, US, CA, Santa Clara +4
What you will do
- Setting the long-term technical vision for distributed AI communication systems—GPU-to-GPU, GPU-to-storage, and cross-node data movement.
- Conducting original research and prototyping next-generation networking solutions over RDMA, NVLink, and GPUDirect.
- Driving hardware-software co-optimization with GPU, DPU, NIC, and network switch. Investigating fundamental bottlenecks in communication runtimes for large-scale AI workloads (KV cache transfer, disaggregated prefill/decode, model parallelism).
- Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM.
- Publishing findings, representing NVIDIA in industry forums and standards bodies, and mentoring senior engineers across the organization.
What you need
- 15+ years in systems software and/or networking with deep expertise in high-performance networking (InfiniBand, RoCE, RDMA, NVLink), communication libraries (e.g. NIXL, NCCL, UCX, MPI, NVSHMEM), and GPU accelerated systems, with track record of defining and delivering complex, cross-team technical initiatives from research concept to production.