Senior Software Engineer, Distributed Systems… at Nvidia · North…

Senior Software Engineer, Distributed Systems Engineer - DGX Cloud Location: US, NC, Remote NVIDIA is hiring experienced software engineers to help scale up its AI Infrastructure. We expect you to have significant software engineering experience with cluster operations, operator development, node health monitoring and working with GPU resource scheduling. We welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications. If you're creative, passionate about GPUs, and love having fun, please apply today! For two decades, we have pioneered visual computing, the art and science of computer graphics. With the invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. What you will be doing: You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. Designing and developing a massively distributed scalable platform which would be used to identify, diagnose and remediate non-performant GPU assets. Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance.  Evaluating system failures and improving services based on a well-defined incident management process. What we need to see: Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work. Highly motivated with strong communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies. 5+ years in similar role and experience on large-scale production systems.  Experience with common software engineering principles, tools and techniques. You possess a BS in Computer Science, Engineering, Physics, Mathematics or a comparable Degree or equivalent experience. Technical knowledge, including a systems programming language (Go, Python) and a solid understanding of data structures and algorithms. Ways to stand out from the crowd: Technical competency in managing and automating large-scale distributed systems independent of cloud providers. Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, Slurm, Base Command Manager). Prior experience in asynchronous workflows and/or event driven architecture. Proven operational excellence in maintaining reliable and performant infrastructure. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until May 14, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. 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. Additional Locations: US, TX, Remote, US, WA, Remote, US, Remote, US, CA, Remote