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Senior Storage Software Engineer, DGXC Data Services

NVIDIA· Engineer, Sys SW
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Hybrid (Santa Clara, CA), Hybrid (Remote (US)), Hybrid (Remote - US), Hybrid (Remote / Local)$152k - $241.5k + equityFull-timePosted 3mo ago

About the role

Senior storage software engineer role at NVIDIA DGXC Data Services building cloud-native storage infrastructure for AI workloads, focusing on high-performance storage paths, observability, and scalable data management across hybrid and multi-cloud environments.

Responsibilities

  • Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure.
  • Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration.
  • Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks.
  • Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads.
  • Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments.
  • Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification.

Qualifications

  • BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience.
  • Strong foundation in algorithms, data structures, distributed systems, operating systems, and practical software design.
  • Experience building performance-sensitive systems, storage, backend, or cloud-native software in languages such as Go, Python, Rust, C/C++, or Java.
  • Experience with storage systems, object stores, caching, Linux systems, Kubernetes, or cloud infrastructure.
  • Ability to reason about performance, scalability, concurrency, reliability, and operational tradeoffs in production systems.
  • Ability to design APIs, document systems, communicate clearly, and break ambiguous infrastructure problems into practical execution plans.
  • Curiosity and practical judgment around AI-assisted or agentic engineering workflows, including using clear intent, specifications, acceptance criteria, tests, and verification to guide development.

Skills

Required:Algorithms and data structuresDistributed systemsStorage systemsLinux systemsKubernetes

Benefits

  • equity
  • benefits (see NVIDIA benefits page)
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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