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Senior Storage Software Engineer - DGX Cloud

NVIDIA· Engineer, Sys SW
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Santa Clara, CA, Hybrid (US (Remote))$224k - $356.5k + equityFull-timePosted 4w ago

About the role

Senior hands-on Storage Software Engineer and technical lead for NVIDIA DGX Cloud storage team, contributing to open-source parallel and distributed file systems, triaging large-scale storage issues, validating architecture and performance, and defining tuning guidelines for GPU-scale deployments.

Responsibilities

  • - Contribute to open-source file systems. contribute code to open-source parallel and distributed file systems, and distributed object storage. Upstream fixes and features, and engage directly with upstream communities and maintainers.
  • - Serve as a hands-on storage software lead. write and review production code, read kernel, NFS, NVMe-oF, or SPDK source to debug bugs, and make final technical calls on storage deliveries against measurable targets.
  • - Triage and troubleshoot at scale. triage, troubleshoot, and root-cause large, complex storage issues across very large GPU clusters (tens of thousands of GPUs) including I/O and metadata performance, data corruption, and recovery.
  • - Validate architecture and capabilities. run scale tests, benchmarks, recovery drills, and qualify new builds against performance and durability targets.
  • - Recommend configuration, tuning, and guidelines. define and promote high-performance file system configurations and operational best practices for GPU infrastructure.
  • - Partner broadly. collaborate with training, inference, SRE, operations, networking, security, cloud providers, and storage vendors on a common architecture.
  • - Work AI-first. leverage AI coding and agentic tools to accelerate building, debugging, validation, and operations.

Qualifications

  • - BS, MS, or PhD in Computer Science, Electrical Engineering, or related field, or equivalent experience.
  • - 12+ years of direct storage software engineering experience with high-performance parallel or distributed file systems at multi-petabyte scale.
  • - Contributions to open-source projects involving a distributed or parallel file system, with hands-on coding, bug analysis, and scale tests.
  • - Experience diagnosing and resolving storage problems in large GPU or HPC clusters, including I/O and metadata performance.
  • - Proficiency in at least one systems language (C, C++, Rust, or Go) and Python; familiarity with Linux kernel storage and networking stacks (block layer, RDMA/RoCE/InfiniBand, NVMe, VFS, multipath).
  • - Solid understanding of object storage (S3/Swift-class) and block storage (NVMe-oF, iSCSI).
  • - Strong written and verbal communication; ability to explain complex trade-offs to engineers, SREs, vendors, and internal customers.
  • - Comfort operating in a 24/7 production environment with a security-first approach.
  • - 100% hands-on engineering: write/review production code, read FS/kernel/NVMe-oF/SPDK sources, and conduct scale tests or recovery drills personally.

Skills

Required:Storage software engineeringC/C++PythonKernel/NVMe-oF/SPDK/NVMeDistributed file systems

Benefits

  • - Equity and benefits per NVIDIA offerings.
Last updated Oct 23, 2026. Interested? Apply on the company site.

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