Senior GPU AI Infrastructure Engineer

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

Job summary

NVIDIA is seeking a senior engineer to scale AI infrastructure, focusing on automating GPU asset provisioning, lifecycle management, and end-to-end data center operations. You will contribute to ML systems at scale, ensuring reliability, performance, and security across distributed hardware and software layers.

You will work with Go, Python, or Rust, on Linux platforms, with Kubernetes/SLURM experience, and collaborate across teams to deliver seamless integration from hardware to AI training

Qualifications

• 12+ years in a similar role on large-scale production systems.
• BS in CS/Engineering/Physics/Mathematics or equivalent.
• Expert level knowledge of Go, Python, or Rust with strong data structures and algorithms.
• Strong Linux system administration
• Deep knowledge of Kubernetes and SLURM in distributed systems.

Responsibilities

• Contribute to a platform that automates GPU asset provisioning across clouds.
• Automate data center management and life-cycle for large-scale ML systems.
• Implement monitoring for reliability, availability, and scalability of GPU assets.
• Process data streams from diagnostics to telemetry for clusters and networks.
• Build automated test infra for distributed systems.
• Collaborate with NVIDIA teams to ensure integration from hardware to AI applications.

Skills

Systems programming

Go

Python

Rust

Linux administration

Distributed systems

Data structures & algorithms

Education

BS in CS/Engineering/Physics/Mathematics or equivalent

Tools

Kubernetes

SLURM

RDMA networking

Job description

NVIDIA is seeking a senior engineer to scale AI infrastructure, focusing on automating GPU asset provisioning, lifecycle management, and end-to-end data center operations. You will contribute to ML systems at scale, ensuring reliability, performance, and security across distributed hardware and software layers.

You will work with Go, Python, or Rust, on Linux platforms, with Kubernetes/SLURM experience, and collaborate across teams to deliver seamless integration from hardware to AI training