Senior AI Infrastructure Engineer — GPU & Datacenter

NVIDIA Corporation; Santa Clara (CA); On-site; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Santa Clara is seeking an experienced Platform Engineer to scale AI infrastructure across GPU datacenters. You will contribute to automated provisioning, lifecycle management, monitoring, and seamless integration from hardware to AI training applications.

We require 12+ years in large-scale production systems, a BS in a related field, and expertise in Go/Python/Rust, Linux, and Kubernetes/SLURM.

Qualifications

• 12+ years of experience in a similar role working on large-scale production systems.
• BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.
• Expert level knowledge of a systems programming language (Go, Python, and/or Rust).
• Strong background in Linux system administration and management.
• Deep knowledge of container orchestration platforms such as Kubernetes and/or SLURM.

Responsibilities

• Contribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.
• Build end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems.
• Implement monitoring and health management capabilities that enable reliability, availability, and scalability of GPU assets.
• Harness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
• Build automated test infrastructure used to qualify distributed systems for operation.
• Partner with engineering teams across NVIDIA to ensure the software integrates seamlessly from the hardware to the AI training applications.

Skills

Go

Python

Rust

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes

SLURM

Linux

Job description

NVIDIA Corporation in Santa Clara is seeking an experienced Platform Engineer to scale AI infrastructure across GPU datacenters. You will contribute to automated provisioning, lifecycle management, monitoring, and seamless integration from hardware to AI training applications.

We require 12+ years in large-scale production systems, a BS in a related field, and expertise in Go/Python/Rust, Linux, and Kubernetes/SLURM.