Systems Software Engineer, Kubernetes Scale - DGX Cloud

The DGX Cloud organization at NVIDIA focuses on delivering accelerated computing solutions for advanced AI workloads by integrating cutting-edge hardware and software innovations.

• 2+ years of experience in Computer Architecture, Networking, Storage systems, Accelerators.
• Bachelor's or Master's degree in Engineering (Electrical, Computer Engineering, Computer Science) or equivalent experience.
• Expertise in Kubernetes and familiarity with CNCF projects.
• Experience with large scale parallel and distributed accelerator-based systems.
• Expertise in optimizing performance and AI workloads on large scale systems.
• Experience with performance modeling and benchmarking at scale.
• Proficiency in Golang and Python.
• Background with NVIDIA software ecosystem in training and inference domains.
• Expertise with at least one public cloud service provider (e.g., GCP, AWS, Azure, OCI).

• Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, including Kubernetes and NVIDIA components.
• Collaborate with AI researchers, developers, and customers to develop automated tests simulating real user workloads.
• Investigate and resolve performance and scale issues in complex distributed systems.
• Design and develop monitoring, reporting, and analysis tools for performance and scale testing.
• Triage, debug, and root cause issues related to operating Kubernetes clusters at ultra-large scale.
• Build and maintain a continuous performance and scale testing framework via CI/CD pipelines.
• Document research, methodologies, and results; present findings at internal and external venues.
• Engage with upstream communities such as Kubernetes, CNCF, and NVIDIA open-source projects to validate performance and scalability.