Join NVIDIA's DGX Cloud team as a Senior AI Infrastructure Engineer. This pivotal role involves designing, building, and maintaining high-availability, large-scale production systems. You'll leverage both software and systems engineering expertise, with a deep understanding of systems, networking, coding, databases, capacity planning, and deployment strategies. Expertise in open-source cloud technologies like Kubernetes and OpenStack is crucial. Your work will ensure maximum reliability and uptime for internal and external GPU cloud services, managing changes with meticulous planning, capacity control, and performance optimization.

NVIDIA fosters a culture of diversity, curiosity, and collaboration. We encourage bold thinking and risk-taking in a supportive, blame-free environment. Our organization values diverse backgrounds and experiences, promoting self-direction on meaningful projects while providing mentorship for professional growth.

Key responsibilities include designing, building, and deploying internal tooling for large-scale AI training and inferencing platforms on cloud infrastructure. You will conduct in-depth performance analysis of multi-GPU and multi-node clusters. Engage in the complete service lifecycle, from inception to operation and refinement. Support pre-launch activities like system design consultation, tool development, capacity management, and launch reviews. Maintain live services by monitoring availability, latency, and overall system health. Scale systems sustainably through automation and drive improvements in reliability and velocity. Practice effective incident response and conduct blameless postmortems. Participate in an on-call rotation to support production systems.

A Bachelor of Science in Computer Science or a related technical field, or equivalent practical experience, is required. Candidates should possess over 5 years of experience, demonstrating a strong balance of project initiation, influencing others, and collaborative teamwork. Proven experience in infrastructure automation and distributed systems design, particularly in developing tools for large-scale cloud systems, is essential. Proficiency in at least one of the following languages is necessary: Python, Go, C/C++, or Java. In-depth knowledge of Linux, Networking, Storage, or Container technologies is also required. Experience with Public Cloud, Infrastructure as Code (IaC) tools like Terraform, and general distributed system expertise are highly valued.