ML Infra Engineer: GPU Clusters & Self-Serve Scale

NVIDIA; Austin (TX); On-site; USD 124,000 - 196,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Software Engineer to accelerate ML innovation by delivering reliable GPU cluster solutions for internal researchers. You will reduce operational toil, enable self-service improvements, and empower scientists to train and deploy advanced ML models on high-performance GPU systems.

Responsibilities include designing scalable engineering solutions, researching AIOps/Agentic AI, and participating in on-call support for owned systems and platforms.

Qualifications

• BS/MS in Computer Science, Engineering, or equivalent.
• 2+ years in software/platform engineering, including 1 year in ML infrastructure or distributed systems.
• Experience on Linux-based platforms and CI/CD pipelines.
• Strong coding skills in Python, C++, or Rust.
• Experience with Docker, Kubernetes, GitLab CI, and automated deployments.
• Experience with AIOps or Agentic AI in production.

Responsibilities

• Design, develop and maintain solutions to validate, monitor and operate GPU clusters at scale.
• Research AIOps and Agentic AI to reduce operational toil.
• Participate in on-call support for systems and platforms.

Skills

Python

C++

Rust

Docker

Kubernetes

GitLab CI

AIOps

Agentic AI

Linux

Education

BS/MS in Computer Science, Engineering, or equivalent

Tools

Slurm

Scheduling frameworks

REST API

Job description

NVIDIA is seeking a Software Engineer to accelerate ML innovation by delivering reliable GPU cluster solutions for internal researchers. You will reduce operational toil, enable self-service improvements, and empower scientists to train and deploy advanced ML models on high-performance GPU systems.

Responsibilities include designing scalable engineering solutions, researching AIOps/Agentic AI, and participating in on-call support for owned systems and platforms.