Senior GPU and HPC Infrastructure Engineer - DGX Cloud

NVIDIA is hiring engineers to scale up its AI Infrastructure. We expect you to have a strong programming background, knowledge of datacenter hardware, operations, and networking, familiarity with software testing and deployment, familiarity with distributed systems, and excellent communication and planning abilities. Experience working with High Performance Computing (HPC), GPUs, and high-performance networking (RDMA, Infiniband, RoCE) are strongly preferred. We also welcome out-of-the-box thinkers who can provide new ideas with a strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You and other engineers on this team will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications that affect core data science. What You Will Be Doing Build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems on a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers. Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets, harnessing multiple data streams from GPU hardware diagnostics to cluster and network telemetry. Work on software that manages NVLINK topography across GPU clusters. Build automated test infrastructure to qualify distributed systems for operation. Work with engineering teams across NVIDIA to ensure your software integrates seamlessly from the hardware all the way up to the AI training applications. Continuously innovate, discover new problems, and design solutions. What We Need To See Highly motivated with strong communication skills, able to work successfully with multi-functional teams, principles, architects, and coordinate effectively across organizational boundaries and geographies. 10+ years of software engineering experience on large-scale production systems. BS in Computer Science/Engineering/Physics/Mathematics or comparable degree or equivalent experience. Expert level knowledge of a systems programming language (Go, Python) and solid understanding of Data Structures and Algorithms. Expert level knowledge of Linux system administration and management. Understanding of cluster management systems such as Kubernetes, SLURM. Understanding of performance, security, and reliability in complex distributed systems; familiarity with system-level architecture, data synchronization, fault tolerance, and state management. Ways To Stand Out From The Crowd Proficiency in architecting and managing large-scale distributed systems, independent of cloud providers; deep knowledge of datacenter operations and GPU hardware; hands‑on experience working with RDMA networking. Advanced hands‑on experience and deep understanding of cluster management systems (Kubernetes, SLURM); hands‑on experience in Machine Learning Operations; hands‑on experience with Bright Cluster Manager. Hands‑on experience developing and/or operating hardware fleet management systems; proven operational excellence in designing and maintaining AI infrastructure. Salary & Benefits Base salary is determined by location, experience, and comparable positions. The range is $184,000 – $287,500 USD for Level 4, and $224,000 – $356,500 USD for Level 5. Eligible for equity and benefits. Applications will be accepted until July 11, 2026. Equal Opportunity NVIDIA is committed to fostering an inclusive work environment and is an equal‑opportunity employer. We do not discriminate based on 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 NVIDIA