- 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, including extensive involvement with a high-performance parallel or distributed file system handling multi-petabyte scale.
- Contributions to open-source projects involving a distributed or parallel file system. You are fully engaged in engineering tasks. You write and review production code, examine file system, kernel, NVMe-oF, or SPDK source to identify bugs, and personally conduct scale tests or recovery drills instead of assigning them to others.
- Experience diagnosing and resolving storage problems in extensive GPU or HPC clusters, including analysis of I/O and metadata performance.
- Strong proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python; comfortable in the Linux kernel storage and networking stacks (block layer, RDMA / RoCE / InfiniBand, NVMe, page cache, VFS, multipath).
- Solid understanding of object storage (S3 / Swift-class) and block storage (NVMe-oF, iSCSI).
- Strong written and verbal communication; capable of clarifying complex technical trade-offs to engineers, SREs, vendors, and internal customers.
- Comfort operating in a 24/7 production environment where storage incidents directly impact GPU availability, with a security-first approach baked into every build.
- 100% hands-on engineering. You write and review production code, read file system, kernel, NVMe-oF, or SPDK source to chase bugs, and run scale tests or recovery drills yourself rather than delegating.
Ways to stand out from the crowd
- Maintainers or sustained contributions to widely used public projects.
- Experience crafting or operating storage for AI training or inference at very large GPU scale, with measurable gains in GPU utilization or reductions in I/O bottlenecks.
- Kernel and file system development experience, metadata scalability, data placement, failure recovery, or HSM or equivalent experience.
- Kubernetes and CSI driver development for storage.
- Hands-on experience with SPDK, libfabric, or FUSE performance optimization.
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence.
NVIDIA is widely considered one of the world's most desirable employers in technology. We have some of the world's most forward-thinking and passionate people working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.