NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA platforms are at the center of generative AI, autonomous driving, industrial robots, medical instruments and data centers across the world where GPU accelerated AI is revolutionizing the technology industry. As a platform company we deliver not just hardware solutions but also vertically integrated software stacks, GPU accelerated SDKs, libraries and tools. As we take our products to market, we need a dedicated and motivated System Software Engineer who is passionate about AI Infrastructure. You will collaborate with engineering, product, and marketing teams to critically assess our hardware and software solutions, elevating the overall product offering and customer experience. You will be working 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 our AI platforms, SDKs, libraries and AI frameworks. Excellent written and verbal communication skills are important. The ability to work independently and the motivation to pick up new technologies and skills will help you excel on the job.
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.
You will also be eligible for equity and benefits.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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