NVIDIA end-to-end network management solutions enable monitoring, management, analytics and visibility. Backed by Sequoia.
About the role
As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. Success in this role requires both operational precision along with developing and supporting forward-looking resource management solutions that address evolving compute demands.
More about this role
As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. Success in this role requires both operational precision along with developing and supporting forward-looking resource management solutions that address evolving compute demands. Beyond day-to-day operations, the role drives improvements in observability, service reliability, and automation, ensuring the EDA compute environment remains resilient, measurable, and aligned with long-term engineering demands.
Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads
Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive measurable improvements in utilization, throughput, and turnaround time
Lead problem solving across scheduler, OS, and workload layers, ensuring timely resolution of service-impacting issues
Identify recurring operational challenges and implement targeted automation or process improvements to reduce manual effort and prevent repeat...
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