Senior Systems Software Engineer - GPU Performance at Scale

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. We are looking for an outstanding engineer for a Senior Performance Engineer role for at scale AI system performance and datacenter applications. Be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing! Provide insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest Accelerated Computing and Deep Learning software and hardware platforms, and with many researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, CPU and GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. What You'll Be Doing Lead all aspects of implementing performance practices in large scale infrastructure, deliver powerful tools, methodologies, and flows to validate and improve several datacenter products in parallel. Specific responsibilities include aligning the next generation AI workloads on top of next generation datacenter designs. This involves early engagement with HW/FW/SW/platform internal and customer teams, and other groups. Deliver engineering solutions to deliver continuous insights into performance of AI workloads over evolving environments, generating quick insights to improvements and regressions over time. Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards final root cause of underlying problems. Participating in engagements with various SW and FW (BMC/SBIOS/OS/drivers etc) teams to develop best-in-class practices and tools, you will be analyzing, debugging and resolving critical firmware and software issues for the best AI workload performance at scale. What We Need To See 8+ years of experience in using accelerated computing for datacenter container computing solutions. Proven understanding of accelerated computing software stacks and DL Frameworks (CUDA, PyTorch). Experience using and handling modern Cloud and container-based Enterprise computing architectures. C/C++/Python/Bash programming/scripting experience. Experience with CPU architecture. Experience with container technology and Linux based OSes. Understanding of collective communication and the patterns in AI workloads. Experience working with engineering or academic research community supporting high performance computing or deep learning. Strong verbal and written communication skills as well as strong teamwork and communication skills. Action driven with strong analytical and analytical skills. BS in Engineering, Mathematics, Physics, or Computer Science, MS or PhD desirable (or equivalent experience). Ways To Stand Out From The Crowd At-scale DL training experience. DL and graph compiling programming skills. Exposure to virtualization techniques, cloud platform solutions. Exposure to scheduling and resource management systems. Experience with large scale HPC environments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until February 14, 2026. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. #J-18808-Ljbffr