Senior Storage Software Engineer - DGX Cloud

Job Title

Senior Storage Software Engineer - DGX Cloud

Role Summary

Hands-on individual contributor and technical lead on NVIDIA's DGX Cloud storage team. Build and maintain high-performance parallel and distributed file and object storage to keep large GPU clusters performant, reliable, and durable.

Work includes writing and reviewing production code, troubleshooting at scale, contributing upstream to open-source projects, and defining configuration and operational best practices.

Experience Level

Senior - typically 12+ years of direct storage software engineering experience (posting specifies over 12 years).

Responsibilities

Deliver and operate storage software for very large GPU/HPC clusters; contribute upstream and lead technical storage deliveries.

• Develop, review, and maintain production code in high-performance distributed and parallel file systems and object storage.
• Contribute upstream fixes and features and engage with open-source maintainers.
• Triage and root-cause large-scale storage incidents (I/O, metadata, corruption, recovery) in multi-thousand to multi-ten-thousand GPU clusters.
• Design and validate storage architecture, run scale tests, benchmarks, and recovery drills against measurable targets.
• Define configuration, tuning, and operational best practices for GPU infrastructure storage.
• Collaborate with training/inference teams, SRE/operations, networking, security, cloud and vendor partners.
• Use modern AI coding and agentic tools to accelerate development, debugging, and validation.

Requirements

Must-have technical skills, experience, and work style.

• Over 12 years of direct storage software engineering experience with extensive involvement in a high-performance parallel or distributed file system at multi-petabyte scale.
• Sustained contributions to open-source distributed or parallel file system projects.
• Proven experience diagnosing and resolving storage issues in large GPU or HPC clusters, including I/O and metadata performance analysis.
• Strong proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python.
• Deep familiarity with Linux kernel storage and networking stacks (block layer, RDMA/RoCE/InfiniBand, NVMe, page cache, VFS, multipath).
• Knowledge of object storage (S3/Swift-class) and block storage (NVMe-oF, iSCSI).
• Ability to operate in a 24/7 production environment; security-first approach; hands-on ownership of code, tests, and incidents.
• Strong written and verbal communication skills for cross-team technical discussions.

Nice-to-have:

• Maintainer or long-term contributor to widely used public projects.
• Experience optimizing storage for AI training/inference at very large GPU scale with measurable impact.
• Kernel and file-system development, metadata scalability, data placement, failure recovery, or HSM experience.
• Kubernetes CSI driver development, SPDK, libfabric, or FUSE performance optimization experience.

Education Requirements

BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field - or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.