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.
Skills Required
- Bachelor’s or master’s degree in Computer Science, Electrical Engineering, or equivalent experience
- 5+ years of experience in compute infrastructure with hands-on batch scheduling responsibility
- Strong practical Slurm experience, including configuration, partitions, QOS, slurmdbd accounting, node management, and production troubleshooting
- Exposure to a second scheduler, preferably LSF, or ability to learn one quickly
- Linux systems administration experience, including filesystems, NFS, networking, processes, and resource management
- Python and shell automation skills
- Experience with monitoring and dashboarding tools
- Semiconductor, EDA, or HPC experience
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
