NVIDIA
Senior Storage Software Engineer - DGX Cloud
$224K–$431K
US, CA, Santa Clara +1 · Senior · Full-time · Posted Oct 11, 2026
- Location
- US, CA, Santa Clara
US, Remote - Experience
- Over 12 years of direct storage software engineering experience.
- Education
- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field — or equivalent experience.
About the job
Develop and operate high-performance storage software and file systems for large GPU clusters, contributing to open source and ensuring performance, reliability, and durability.
What you'll do
- Contribute code and upstream fixes and features to open-source parallel and distributed file systems and distributed object storage.
- Write and review production code; troubleshoot storage issues at scale and validate performance and durability through tests and recovery drills.
- Set storage configuration and tuning practices, and collaborate with engineering, operations, cloud, and storage partners.
What they ask for
- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field — or equivalent experience.
- Over 12 years of direct storage software engineering experience, including extensive work with a high-performance parallel or distributed file system at multi-petabyte scale.
- Open-source contributions involving a distributed or parallel file system; experience diagnosing storage issues in large GPU or HPC clusters.
- Proficiency in at least one of C, C++, Rust, or Go, and in Python; Linux kernel storage and networking stack familiarity; understanding of object and block storage.
Nice to have
- Maintainer status or sustained contributions to widely used public projects; storage experience for AI workloads at very large GPU scale.
- Kernel or file system development, Kubernetes and CSI driver development, or hands-on SPDK, libfabric, or FUSE performance optimization.
Pay
224,000 USD - 356,500 USD (base salary, Level 5); 272,000 USD - 431,250 USD (base salary, Level 6)
Tools
C, C++, Rust, Go, Python, Linux, NVMe-oF, SPDK
AI focus
Use modern AI coding and agentic tools day-to-day to accelerate building, debugging, validation, and operations.
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