Distinguished Engineer, Storage, AI Cloud

What you'll do

• Lead the multi-year technical plan and reference architecture for AI Cloud storage expansion across Neocloud and Cloud Service Providers.
• Direct the architecture of high-performance parallel file systems, object stores, and block storage at exabyte scale.
• Define production-ready standards for durability and availability SLOs while ensuring sustained efficiency and observability.
• Develop prototype reference implementations and make final technical decisions on storage deliveries for external partners.
• Establish and guide an open-source strategy for AI storage, including formalizing APIs, SDKs, and protocols.
• Design storage layers for next-generation GPU workloads, including disaggregated inference and large-scale regional object stores.
• Mentor senior and principal engineers while representing NVIDIA in external standards bodies and industry forums.
• Automate all infrastructure management tasks, including live software upgrades, capacity rebalancing, and cross-DC data movement.

What we're looking for

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
• Minimum of 18+ years of practical engineering experience in storage technology.
• Extensive experience with high-performance parallel file systems like Lustre, GPFS, WEKA, VAST, BeeGFS, or DAOS at multi-petabyte scale.
• Wide-ranging expertise in object storage (S3/Swift-class) and block storage (NVMe-oF, NVMesh-class, iSCSI).
• Track record of managing storage platforms at exabyte scale for AI training, HPC, or hyperscale data lakes with 9s SLOs.
• Strong proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python.
• Proficiency in Linux kernel storage and networking stacks, including RDMA/RoCE/InfiniBand, NVMe, page cache, VFS, and multipath.
• Proven background in designing storage solutions for AI training or inference at 10k+ GPU scale (preferred).