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Senior Slurm Administrator

Nvidia

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  1. Why do you want to join Nvidia?
  2. What is your experience with Accounting? Tell me one thing you learned the hard way.
  3. Which numbers do you track every day, and why those?
  4. Tell me about a process you made faster or cheaper.
  5. How do you handle a delay that affects a customer?

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NVIDIA is looking for an exceptional engineer to grow and thrive alongside our HPC Infrastructure team that designs, evaluates, and optimizes the compute infrastructure powering NVIDIA's next-generation silicon design and AI workloads. You'll own Slurm within NVIDIA's VLSI compute environment and provide second-deep coverage across the wider scheduling estate. What you'll be doing: In this position, you will own Slurm within NVIDIA's VLSI compute environment and provide second-deep coverage across the wider scheduling estate. Administer, configure and tune Slurm clusters - partitions, QOS, accounting, limits, node states and topology - and operate them alongside an existing LSF estate. Automate scheduler operations: node onboarding and draining, configuration management, health checks and routine maintenance. Build and maintain dashboards and reporting for job throughput, queue wait times and SLA attainment. This is a hands-on technical role. You will be in the cluster and the scripts yourself, supporting design engineers during local business hours, and day-to-day operations - queue health and job triage - are a core part of the job rather than a side activity. What we need to see: B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or equivalent experience. 5+ years in compute infrastructure, with hands-on responsibility for batch scheduling. Strong practical Slurm experience: configuration, partitions and QOS, accounting via slurmdbd, node management, and troubleshooting real job failures in production. Exposure to a second scheduler, LSF preferred, or a clear appetite to pick one up quickly. Solid Linux systems administration - filesystems, NFS, networking, process and resource management. Working automation skills in Python and shell, and experience with monitoring and dashboarding tools. Comfortable carrying a real operational load - you treat production support and escalations as part of the engineering job. Semiconductor/EDA or HPC exposure is a plus, not a requirement.

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Listed on workday · posted 2026-10-13. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.