NVIDIA is on the journey to build the best cloud offering for AI workloads and to bring its latest GPU technology to our clients as a set of managed services under the DGX Cloud umbrella. We want to be able to innovate on behalf of our clients and provide an easy, no-hassle way of using the latest and greatest NVIDIA products through scalable managed self-service APIs. We are looking for a Cloud Platform Engineer to drive the technical design and build foundational elements of our high-performing cloud services for Artificial Intelligence and high-performance computing. This is a unique opportunity to be a founding member of a team building at the intersection of a highly scalable fault-tolerant cloud services and AI.If you are passionate about IaC and you can argue why declarative infra is the way to go, can explain Kubernetes PDB to your family in under 5 minutes, or If you always felt that Kubernetes is great, but this not the ultimate goal and always wanted to extend it and turn into the distributed operating system for AI, you are a perfect fit to join our team!What you'll be doing:As a part of the service team, build and design platforms for DGX Cloud servicesFigure out how to take best from HPC and Kubernetes and help us make the unified platformWork within the team of software engineers and product people as well as engineering teams across all of NVIDIA on DGX Cloud AI Compute servicesWrite IaC code, work on Kubernetes, and help the team to design and implement release pipelinesCollaborate to understand how to make the best use of GitOps and PipelinesWhat we need to see:BS in Computer Science, Information Systems, Computer Engineering or equivalent experienceSolid technical foundation in distributed computing and storage, including substantial experience with all of the following: server systems, storage, I/O, networking, and system software12+ years of platform engineering experience on large-scale production systemsKubernetes and IaC expertise as an engineerAbility to understand and communicate complex designs, distributed infrastructure, and requirements to peers, customers, and vendorsGeneral shared storage knowledge such as NFS, LustreFS, GlusterFS, etc.Familiarity with system-level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO.Ways to stand out from the crowd:Proven experience in high performance computing, Deep Learning, and/or GPU accelerated computing domainsLarge-scale distributed system, HPC, ML and Training experience with Slurm and KubernetesDeep knowledge of both software and hardware knowledge in HPC and ML infrastructureNVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence.Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.You will also be eligible for equity and benefits.Applications for this job will be accepted at least until September 22, 2025.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.