Senior AI Storage Systems Engineer

NVIDIA; United States; On-site; USD 152,000 - 287,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA DGXC Data Services team builds cloud-native data systems spanning hybrid and multi-cloud environments to enable scalable AI training and inference on exabytes of data.

We seek engineers who can design storage technologies, optimize performance, and implement robust observability with production-grade reliability. You will collaborate with internal AI teams, platform groups, and SRE to deliver durable data infrastructure.

Qualifications

• BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience.
• Strong foundation in algorithms, data structures, distributed systems, and operating systems.
• Experience building performance-sensitive storage or cloud-native software.
• Experience with Go, Python, Rust, C/C++ or Java in production.
• Familiarity with Linux systems and Kubernetes.

Responsibilities

• Build storage technologies, client libraries, and filesystem frameworks for AI workloads.
• Develop high-performance storage paths for training and inference workflows.
• Build observability systems to diagnose storage bottlenecks and expose telemetry.
• Improve performance, scalability, and reliability of large-scale storage systems.
• Collaborate with AI, platform, SRE, and operations teams to validate storage behavior.
• Apply modern engineering practices with emphasis on design, testing, and security.

Skills

Go

Python

Rust

C/C++

Java

Distributed systems

Algorithms

Operating systems

APIs design

Performance optimization

Education

BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience

Tools

Kubernetes

Linux

FUSE

Cloud infrastructure

Job description

NVIDIA DGXC Data Services team builds cloud-native data systems spanning hybrid and multi-cloud environments to enable scalable AI training and inference on exabytes of data.

We seek engineers who can design storage technologies, optimize performance, and implement robust observability with production-grade reliability. You will collaborate with internal AI teams, platform groups, and SRE to deliver durable data infrastructure.