The Role
Own the operational health, performance, efficiency, and observability of a large Linux compute farm supporting VLSI design and AI workloads. Diagnose kernel, filesystem, memory, I/O, NFS, and workload issues; improve resource utilization; build telemetry, metrics, dashboards, and license alerts; and provide hands-on operational triage for compute users.
Summary Generated by Built In
NVIDIA is looking for an exceptional engineer to grow and thrive alongside our Infrastructure team that designs, evaluates, and optimizes the compute inrastructure powering NVIDIA's next-generation silicon design and AI
workloads.You will own the operational health, efficiency and observability of a large Linux compute farm serving NVIDIA's VLSI design teams
What you'll be doing:
- In this position, you will own the operational health, efficiency and observability of a large Linux compute farm serving NVIDIA's VLSI design teams, and be the person who can say where the time and the capacity are actually going.
- Profile and debug at the system level - kernel, filesystem, memory and I/O behaviour - when workloads are slow, and turn findings into fixes rather than tickets.
- Drive compute efficiency: memory request-versus-usage accuracy, CPU waste from idle and over-provisioned jobs, and the prediction models behind resource requests.
- Build the observability layer for the farm - telemetry pipelines, metrics and dashboards that make capacity, utilisation and job behaviour visible to engineers and to leadership - and own licence monitoring and expiry alerting across the EDA tool estate.
- This is a hands-on technical role. Day-to-day farm operations and live triage are a core part of it, and you will work directly with the heaviest users on their workload behaviour, since most efficiency gains come from a small number of workflows.
What we need to see:
- B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or equivalent experience.
- 8+ years in Linux systems administration or infrastructure operations at scale.
- Deep Linux systems and kernel-level expertise - comfortable with perf, eBPF/bpftrace, strace, cgroups, NUMA, memory management, scheduler behaviour and I/O subsystems, and able to use them to find root cause rather than guess at it.
- Demonstrated experience diagnosing and fixing performance problems on large multi-user compute systems.
- Strong NFS and distributed filesystem troubleshooting: metadata versus data path, client behaviour, mount and latency issues.
- Hands-on experience building observability - time-series metrics, log and telemetry pipelines, and dashboards (Prometheus/Grafana, Elastic, or equivalent) - plus strong Python for analysis and automation.
- Familiarity with batch schedulers (LSF, Slurm, or equivalent) and job resource accounting, and a genuine appetite for operational work. Semiconductor/EDA or HPC background is a plus.
Skills Required
- B.E., B.Tech, M.Tech in Computer Science, Electrical Engineering, or equivalent experience
- 8+ years of experience in Linux systems administration or infrastructure operations at scale
- Deep Linux systems and kernel-level expertise, including perf, eBPF/bpftrace, strace, cgroups, NUMA, memory management, scheduler behavior, and I/O subsystems
- Experience diagnosing and resolving performance problems on large multi-user compute systems
- Strong NFS and distributed filesystem troubleshooting experience
- Experience building observability solutions using time-series metrics, log and telemetry pipelines, and dashboards
- Experience with Prometheus, Grafana, Elastic, or equivalent observability tools
- Strong Python skills for analysis and automation
- Familiarity with batch schedulers such as LSF, Slurm, or equivalent
- Experience with job resource accounting and operational support
- 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.
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The Company
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.”
