Senior System Software Engineer, AI Infrastructure

NVIDIA•Santa Clara, CA

1d•$124,000 - $241,500

About The Position

NVIDIA is transforming computer graphics, PC gaming, and accelerated computing, and is now tapping into the unlimited potential of AI to define the next era of computing. NVIDIA platforms are at the center of generative AI, autonomous driving, industrial robots, medical instruments, and data centers worldwide, where GPU-accelerated AI is revolutionizing the technology industry. As a platform company, NVIDIA delivers not just hardware solutions but also vertically integrated software stacks, GPU-accelerated SDKs, libraries, and tools. This role is for a dedicated and motivated System Software Engineer passionate about AI Infrastructure. You will collaborate with engineering, product, and marketing teams to critically assess hardware and software solutions, elevating the overall product offering and customer experience. You will work in a multifaceted environment engaging with multiple groups within the company to improve NVIDIA’s developer products. You will use your system and application development knowledge to evaluate user experience and performance of NVIDIA's AI platforms, SDKs, libraries, and AI frameworks. Excellent written and verbal communication skills are important, as is the ability to work independently and a motivation to pick up new technologies and skills.

Requirements

Passionate about AI infrastructure and performance optimization.
3+ years in software development, tech marketing, evangelism, or similar roles.
BS/MS in CS, CE, EE, or related field (or equivalent experience).
Strong Python and C++ skills for AI and HPC work.
Hands-on multi-node experience with Slurm, Kubernetes, or cloud CSP clusters.
Solid grasp of DL architectures, PyTorch, and distributed training methods.
Understanding of CPU/GPU architecture plus CUDA, cuDNN, TensorRT-LLM, Triton, NCCL.
Excellent written and verbal communication for technical and executive audiences.

Nice To Haves

Hands-on experience setting up and tuning HPC clusters with Slurm, Kubernetes, or other schedulers.
Public technical blogs, talks, forum activity, or notable open-source projects.
Prior work with customers and/or technical press on AI performance topics.
Exceptional communication skills that simplify complex technology for diverse audiences.
Familiarity with modern LLM architectures and ability to write Torch code and occasional custom GPU kernels.
Expertise in InfiniBand, NVLink, RoCE, RDMA, and collective-comm libraries.

Responsibilities

Run multi-node training/inference jobs on large GPU clusters to assess performance, validate usability, improve products, and create developer education.
Design benchmark suites that spotlight NVIDIA hardware, networking, and software stacks.
Profile deep-learning workloads, identify bottlenecks, and deliver optimization guidance.
Produce concise tutorials, scripts, and whitepapers for customers and tech press.
Analyze competitive solutions and craft data-driven product positioning.
Present live demos at GTC, CES, SIGGRAPH, and other global conferences.