Senior Storage Software Engineer

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CANCTXWA
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 11 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $209k

This role $197k

$139k $272k

below market most similar roles pay here above market

This role pays less than 62% of similar roles. Most pay $176,937–$241,750 — the blue band above. At the midpoint, this role pays about $197k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Storage Software Engineer

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The Senior Storage Software Engineer, DGXC Data Services joins the DGXC Data Services team to build cloud-native systems and frameworks for managing data across hybrid and multi-cloud infrastructure. This role involves developing storage technologies, client libraries, and filesystem frameworks to support AI workloads, including data loading, checkpointing, caching, and POSIX-style access. You will build observability systems to diagnose storage bottlenecks and attribute GPU idle time to I/O behavior while improving performance for massive datasets and high-concurrency workloads. Required skills include proficiency in Go, Python, Rust, C/C++, or Java, along with experience in distributed systems, operating systems, Kubernetes, and Linux. You will solve complex problems regarding storage, access, ingestion, and governance for high-performance GPU-based training and inference jobs at an exabyte scale.

Skills

Go Python Rust C/C++ Java Kubernetes Linux Distributed Systems FUSE POSIX eBPF Cloud Infrastructure Telemetry High-Performance Computing Data Pipelines

What you'll do

Build storage technologies, client libraries, and filesystem frameworks for hybrid and multi-cloud infrastructure.
Develop high-performance storage paths for AI training and inference, including data loading and checkpointing.
Build observability systems to diagnose storage bottlenecks and attribute GPU idle time to I/O behavior.
Improve performance, scalability, and reliability of storage systems serving massive datasets and high-concurrency workloads.
Validate storage behavior against real workloads by working with internal AI, platform, and SRE teams.
Implement modern software engineering practices, including AI-assisted and agentic development workflows.
Design APIs and document systems to break ambiguous infrastructure problems into practical execution plans.

What we're looking for

BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience.
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 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, and break ambiguous infrastructure problems into practical execution plans.
Background with Linux kernel observability, eBPF, tracing, or low-overhead telemetry systems (preferred).

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