Senior Linux Administrator
NVIDIA · Posted Oct 13
Graphics processing units, artificial intelligence platforms, accelerated computing, and data center solutions
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About the role
NVIDIA's Infrastructure team designs, evaluates, and optimizes the compute infrastructure powering NVIDIA's next-generation silicon design and AI workloads. This role owns the operational health, efficiency, and observability of a large Linux compute farm serving NVIDIA's VLSI design teams. The engineer will profile and debug system-level performance, drive compute efficiency, and build telemetry, metrics, and dashboards for the farm.
What you will do
- 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.
Skills used in this role
What the employer is looking for
- 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.
Benefits and support
- Compensation and benefits are detailed in the job posting
About NVIDIA
NVIDIA Corporation is a multinational technology company that designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market. Pioneering accelerated computing, the company has become a driving engine of modern artificial intelligence, deep learning, and data center infrastructure.
- Industry
- Semiconductors
- Company size
- 42000+ employees
- Founded
- April 5, 1993
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company · $5M raised
Leadership
Founder, President and Chief Executive Officer
Executive Vice President and Chief Financial Officer
Founder and NVIDIA Fellow
Executive Vice President, Worldwide Field Operations
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