Teams at NVIDIA

Leads engineering enablement for large-scale AI/HPC clusters, managing a support team, training and documentation, request intake and prioritization, specialist debugging coordination, and user community development. Partners across architecture, software, firmware, networking, storage, datacenter operations, performance, and program teams. Uses service metrics and user feedback to improve workflows, self-service guidance, resource allocation, and support quality.

Investigate, assess, and remediate vulnerabilities across NVIDIA data center platforms. Responsibilities include vulnerability triage, exploitability analysis, CVSS and CWE assessment, security fixes, regression testing, dependency updates, automation, and coordinated disclosure. The role also improves secure development lifecycle practices through threat modeling, security reviews, testing, and security automation while collaborating across distributed engineering teams.

Leads engineering teams developing platform software for GPU-accelerated applications using Kubernetes, container runtimes, Kata Containers, and Confidential Containers. Responsibilities include enabling GPUs as Kubernetes resources, integrating software across NVIDIA’s technology stack, managing priorities, and delivering secure, reliable distributed systems. The role requires deep systems software expertise, engineering management experience, and hands-on knowledge of containers, Linux, cloud computing, virtualization, and confidential computing technologies.