Senior System Software Engineer, AI Infrastructure

What You’ll Be Doing

• 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.

What We Need To See

• 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.

Ways To Stand Out From The Crowd

• 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 as well as 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.