Drimva

NVIDIA

Senior Storage Production Engineer - DGX Cloud

$176K–$334K

US, CA, Santa Clara +1 · Senior · Full-time · Posted Aug 5, 2026

Location
US, CA, Santa Clara
US, Remote
Experience
8+ years of practical experience.
Education
BS degree or equivalent experience in Computer Science, Storage Systems, or a related technical field.

About the job

Designs, operates, and optimizes large-scale storage systems for NVIDIA’s GPU cloud services and AI/ML workloads, focusing on reliability, performance, automation, and data integrity.

What you'll do

  • Design, implement, and support scalable, highly available storage clusters; monitor system health and resolve performance issues.
  • Improve storage architecture and efficiency for AI/ML workloads through caching, tiering, compression, deduplication, and workload placement.
  • Automate storage operations and support service lifecycle activities, capacity management, incident response, and on-call coverage.

What they ask for

  • BS degree or equivalent experience in Computer Science, Storage Systems, or a related technical field.
  • Experience with distributed and high-performance storage solutions, storage technologies, and storage networking protocols.
  • Expertise in algorithms, data structures, software design, and automating large-scale Linux-based storage systems.
  • Experience with one or more of C/C++, Java, Python, Go, NodeJS, and Bash; configuration management and observability tools are also specified.

Nice to have

  • Knowledge of distributed storage replication and erasure coding, capacity planning, and performance troubleshooting.
  • Experience with Git, code review, CI/CD, cloud storage, Kubernetes, OpenStack, or hybrid cloud architectures.

Pay

176,000 USD - 276,000 USD (base salary, Level 4); 208,000 USD - 333,500 USD (base salary, Level 5)

Tools

NFS, SMB, iSCSI, S3, Fibre Channel, RDMA, NVMe over Fabrics, Linux

AI focus

Optimizes storage for AI/ML workloads and uses predictive analytics and AI-driven automation for storage operations and scaling.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)