Jobs / India / Nvidia Corporation
Senior Linux Administrator
Nvidia Corporation · 🌍 India, Bengaluru
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About the role
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.