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Senior Slurm Administrator - India, Bengaluru | Nvidia Job


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Job Opportunity Details

Type

Full Time

Salary

Not Telling

Work from home

No

Weekly Working Hours

Not Telling

Positions

Not Telling

Working Location

India, Bengaluru, India, India   [ View map ]

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.





More Information

Application Details

  • Organization Details
    Nvidia
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