Senior Storage Engineer — Cloud-Native AI Data Infrastructure

NVIDIA; California (MO); On-site; USD 184,000 - 287,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We solve problems in AI data management for exabyte-scale, high-performance GPU workloads.

We are seeking engineers to develop storage technologies, APIs, and observability to improve performance and reliability for AI training and inference at scale. Strong foundations in distributed systems, OS, and languages like Go, Python, Rust, C/C++, or Java

Qualifications

• 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 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.

Responsibilities

• Build storage technologies, client libraries, and filesystem frameworks for AI workloads across object stores, file systems, and hybrid cloud.
• Develop high-performance storage paths for training and inference, including data loading, checkpointing, caching, POSIX access, and object-store integration.
• Build observability systems that diagnose storage bottlenecks and expose telemetry through production monitoring stacks.
• Improve performance, scalability, and reliability of storage systems handling massive datasets and high-concurrency workloads.
• Collaborate with internal AI teams, platform teams, SRE, and operations to validate storage against real workloads and production environments.
• Use modern software engineering practices, including AI-assisted workflows, with high standards for design, testing, security, performance and verification.

Skills

Algorithms

Distributed systems

Operating systems

Go

Python

Rust

C/C++

Java

Linux

Kubernetes

Cloud infrastructure

API design

Documentation

AI-assisted workflows

Education

BS in Computer Science

Equivalent experience

Tools

Go tooling

Python tooling

Job description

NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We solve problems in AI data management for exabyte-scale, high-performance GPU workloads.

We are seeking engineers to develop storage technologies, APIs, and observability to improve performance and reliability for AI training and inference at scale. Strong foundations in distributed systems, OS, and languages like Go, Python, Rust, C/C++, or Java