Senior Storage Software Engineer

Nvidia

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$224,000–$356,500 / yr
Posted
4 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $195k
This role $290k
$127k most similar roles pay here $381k

This role pays more than 95% of similar roles. Most pay $162,050–$228,787 — the shaded band above. At the midpoint, this role pays about $290k versus about $195k 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 867 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 849 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Storage Software Engineer

Senior Storage Software Engineer - DGX Cloud joins the DGXC Storage team to serve as a hands-on technical lead and individual contributor. This role involves contributing to open-source parallel and distributed file systems and distributed object storage while maintaining high-performance GPU clusters. Responsibilities include writing and reviewing production code, triaging complex I/O and metadata issues at scale, performing recovery drills, and defining configuration standards for large-scale infrastructure. The candidate will work with kernel, NVMe-oF, and SPDK source code to resolve bugs and ensure data durability. Required skills include proficiency in C, C++, Rust, or Go, along with Python expertise. Candidates must navigate Linux kernel storage and networking stacks, including RDMA, RoCE, InfiniBand, and VFS. The role addresses the critical challenge of maintaining high-performance storage for large-scale AI training and inference workloads across cloud environments.

What you'll do

  • Contribute code and upstream fixes to open-source parallel, distributed file systems, and object storage.
  • Write and review production code while analyzing kernel, NFS, NVMe-oF, or SPDK source to resolve bugs.
  • Triage and root-cause complex I/O performance, data corruption, and recovery issues across large GPU clusters.
  • Validate storage architecture, capabilities, and durability through scale tests, benchmarks, and recovery drills.
  • Define and recommend configuration, tuning, and operational best practices for high-performance file systems on GPU infrastructure.
  • Make final technical decisions on storage deliveries against measurable performance and reliability targets.
  • Utilize modern AI coding and agentic tools to accelerate development, debugging, and validation tasks.

What we're looking for

  • BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
  • Over 12 years of direct experience in storage software engineering with high-performance parallel or distributed file systems at multi-petabyte scale.
  • Experience contributing to open-source projects involving distributed or parallel file systems.
  • Proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python.
  • Expertise in Linux kernel storage and networking stacks including block layer, RDMA/RoCE/InfiniBand, NVMe, page cache, VFS, and multipath.
  • Solid understanding of object storage (S3/Swift-class) and block storage (NVMe-oF, iSCSI).
  • Experience diagnosing and resolving storage problems in large GPU or HPC clusters involving I/O and metadata performance.
  • Strong written and verbal communication skills to explain complex technical trade-offs to various stakeholders.

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