Senior Linux Administrator

NVIDIA; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

NVIDIA in Bengaluru seeks an experienced Linux systems engineer to own the observability and efficiency of a large compute farm supporting VLSI design teams. You’ll diagnose performance and scale challenges, build telemetry pipelines, and collaborate with users to drive fixes.

You’ll work hands-on with kernel, memory, I/O subsystems, and batch schedulers, applying Python to automate analysis and dashboards, ensuring reliability and proactive capacity planning.

Qualifications

• 8+ years in Linux systems administration or infrastructure operations at scale.
• Deep Linux kernel and system-level expertise (perf, eBPF/bpftrace, strace, cgroups, NUMA, memory management, schedulers, I/O).
• Experience diagnosing performance problems on large multi-user compute systems.
• Strong troubleshooting of NFS and distributed filesystems.

Responsibilities

• Own the operational health, efficiency and observability of a large Linux compute farm serving NVIDIA's VLSI design teams.
• Profile and debug at the system level (kernel, filesystem, memory, I/O) when workloads are slow and implement fixes.
• Drive compute efficiency: memory request vs usage, CPU waste, and resource-prediction models.
• Build the observability layer: telemetry pipelines, metrics and dashboards (Prometheus/Grafana, Elastic) and license monitoring.
• Hands-on day-to-day farm operations and live triage, collaborating with heaviest users on workload behavior.

Skills

Linux administration

Perf tools

eBPF/bpftrace

Strace

Cgroups

NUMA

Memory management

Schedulers

I/O subsystems

Root cause analysis

Observability

Python

Prometheus

Grafana

Batch schedulers

LSF

Slurm

HPC background

Education

B.E./B.Tech./M.Tech in Computer Science or Electrical Engineering

Tools

Prometheus

Grafana

Elastic

Job description

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.