NVIDIA
Senior Software Engineer, DGX Cloud AI Infrastructure
$184K–$356K
US, CA, Santa Clara +4 · Senior · Full-time · Posted Sep 29, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, OR, Remote
US, WA, Remote
US, WA, Redmond - Experience
- 8+ years; no alternatives stated.
- Education
- Bachelor’s or Master’s in Computer Science or a related technical field (or equivalent experience).
About the job
Leads the bring-up, benchmarking, performance optimization, and reliability work for large-scale distributed AI training and inference workloads on NVIDIA GPU platforms.
What you'll do
- Validate, debug, and optimize large-scale AI clusters and end-to-end workloads.
- Build benchmark, qualification, resilience, and failure-attribution capabilities for GPU clusters.
- Set technical direction, mentor engineers, and provide data-driven performance recommendations.
What they ask for
- Bachelor’s or Master’s in Computer Science or a related technical field (or equivalent experience).
- 8+ years of experience developing software infrastructure for large-scale AI or HPC systems, including a track record of technical leadership.
- Deep hands-on experience with NCCL, CUDA-aware distributed execution, and debugging multi-GPU and multi-node workloads at scale.
- Expert-level Python and C/C++ programming skills.
Nice to have
- Deep familiarity with the RDMA software stack (NCCL, IB verbs, UCX, libfabric).
- Strong knowledge of GPU cluster fabrics and topology, including NVLink, NVSwitch, PCIe, RoCE, and InfiniBand.
Pay
184,000 USD - 287,500 USD (base salary); 224,000 USD - 356,500 USD (base salary)
Tools
PyTorch, NeMo / Megatron, TensorRT-LLM, Nsight Systems, NCCL, CUDA, Python, C/C++
AI focus
Bring up, benchmark, analyze, and optimize large-scale AI pre-training, post-training, and inference workloads, including distributed LLM workloads.
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