Senior HPC Storage Engineer, EDA Infrastructure

Nvidia

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k
This role $236k
$136k $304k
below market most similar roles pay here above market

This role pays more than 82% of similar roles. Most pay $155,675–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $196k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior HPC Storage Engineer, EDA Infrastructure

As a Senior HPC Storage Engineer - EDA Infrastructure, you will join the HW Infrastructure Storage Strategy team to bridge the gap between storage infrastructure and chip design workloads. You will evaluate next-generation storage technologies, design proofs of concept using real EDA workload profiles, and identify gaps in observability. Your daily responsibilities include analyzing how storage configurations impact EDA runtime, defining data lifecycle policies, and supporting datacenter lifecycle programs. You will utilize technologies including NetApp, VAST, Lustre, GPFS, Ceph, and Weka within Linux environments. Required skills include Python, Bash scripting, and experience with observability tools like Prometheus and Grafana. You will solve complex problems regarding petabytes of active data and millions of files per job to improve engineering velocity for AI and cloud-hybrid infrastructure.

What you'll do

  • Design and execute POCs for storage platforms using real EDA workload profiles to benchmark performance.
  • Analyze how storage configurations impact EDA workload runtime and recommend architectural changes to reduce execution time.
  • Identify gaps in storage telemetry and define metrics to correlate storage behavior with running jobs.
  • Support datacenter lifecycle programs by mapping workload placement and minimizing data replication scope.
  • Define storage policies for data lifecycle, tiering strategies, snapshot workflows, and capacity planning.
  • Investigate production storage issues to characterize impacts, identify root causes, and recommend preventive measures.
  • Contribute to the long-term storage strategy and roadmap for next-generation compute and AI workloads.

What we're looking for

  • Bachelor’s degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
  • 8+ years of experience with large-scale NFS and networked storage systems in Linux environments.
  • Hands-on experience with at least one enterprise or HPC storage platform such as NetApp, VAST, Pure, Lustre, GPFS, Ceph, or Weka.
  • Strong Linux systems skills and the ability to perform storage performance analysis to characterize workload outcomes.
  • Proficiency in Python and Bash scripting for automation and tooling.
  • Experience with cloud-based storage solutions such as GCP Filestore, NetApp Cloud Volumes, or AWS FSx.
  • Experience with observability and metrics collection systems like Prometheus, Grafana, or Netdata.
  • Experience with EDA infrastructure, semiconductor design workflows, or container technologies (preferred).

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