Senior Storage Software Engineer (DGX Cloud)

Quick Facts

• Role: Senior Storage Software Engineer (hands-on technical lead) for DGX Cloud storage

• Focus: Open-source parallel/distributed file systems and distributed object storage, production incident triage, performance/durability validation, and fleet configuration standards

Description

You will contribute to open-source parallel and distributed file systems and distributed object storage, and upstream fixes and features with community maintainers. As a hands-on storage software lead, you will write and review production code, read kernel/NFS/NVMe-oF/SPDK source when needed, and make technical calls against measurable storage delivery targets. You will triage and root-cause storage issues at tens of thousands of GPU scale, validate architecture with scale tests/benchmarks and recovery drills, and define tuning and operational best practices for high-performance GPU infrastructure.

Responsibilities

• Contribute to open-source parallel/distributed file systems and distributed object storage; upstream fixes/features

• Write and review production code; debug using kernel and storage stack sources

• Triage and root-cause large storage incidents across GPU clusters (I/O/metadata, corruption, recovery)

• Validate storage architecture and durability/performance via scale tests, benchmarks, and recovery drills

• Recommend configuration, tuning, and operational guidelines for GPU-based file systems

• Partner with training/inference, SRE/operations, networking, security, and storage/cloud/neocloud stakeholders

• Use modern AI coding/agentic tools to accelerate building, debugging, validation, and operations

Requirements

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field OR equivalent experience

• 12+ years of direct storage software engineering experience, including multi-petabyte parallel/distributed file system work

• Active open-source contributions to distributed/parallel file systems; write/review production code and personally conduct scale tests/recovery drills

• Experience diagnosing/resolving storage problems in large GPU or HPC clusters with I/O and metadata performance analysis

• Strong systems-language proficiency (C/C++/Rust/Go) and Python proficiency

• Comfortable with Linux kernel storage/networking stacks (block layer, RDMA/RoCE/InfiniBand, NVMe, page cache, VFS, multipath)

• Understanding of object storage (S3/Swift-class) and block storage (NVMe-oF, iSCSI)

• Strong communication skills to clarify complex technical trade-offs

• Comfortable with 24/7 production operations where storage incidents impact GPU availability; security-first approach

• 100% hands-on engineering mindset (no delegation of debugging/tests)

Benefits

• Base salary range for senior levels; eligibility for equity and benefits

• Opportunity to build foundational storage capabilities for the AI era on large GPU fleets