Senior AI Infrastructure Engineer - DGX Cloud

at Nvidia

📍 United States

USD 152,000-287,500 per year

SENIOR

✅ Remote

Tech Stack
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AI Communication @ 7 Distributed Systems @ 4 GPU Go @ 4 IaC Java @ 4 Kubernetes @ 4 Linux @ 4 Mathematics @ 4 Networking @ 4 OpenStack Performance Optimization Python @ 4 Slurm @ 4 Terraform @ 4

Details

NVIDIA is seeking a Senior AI Infrastructure Engineer to join the DGX Cloud group. The role focuses on designing, building, deploying, and maintaining large-scale production systems for AI training and inference with high efficiency, reliability, and availability. It combines software and systems engineering across networking, coding, databases, capacity management, continuous delivery and deployment, Kubernetes, OpenStack, and other open-source cloud-enabling technologies.

The DGX Cloud Production Engineer helps ensure GPU cloud services deliver maximum reliability and uptime through careful change planning, capacity management, and performance optimization. The team values diversity, curiosity, problem-solving, openness, collaboration, self-direction, and continuous learning.

Responsibilities

Design, build, deploy, and operate internal tooling for large-scale AI training and inference platforms built on cloud infrastructure.
Conduct in-depth performance characterization and analysis of large multi-GPU and multi-node clusters.
Improve the full service lifecycle, from inception and design through deployment, operation, and refinement.
Support services before launch through system design consulting, software tools, platforms, frameworks, capacity management, and launch reviews.
Maintain live services by measuring and monitoring availability, latency, and overall system health.
Scale systems sustainably through automation and drive changes that improve reliability and delivery velocity.
Practice sustainable incident response and conduct blameless postmortems.
Participate in an on-call rotation supporting production systems.

Requirements

Bachelor's degree in Computer Science or a related technical field involving coding, such as physics or mathematics, or equivalent experience.
5+ years of experience.
A track record of initiating projects, gaining collaboration, and working effectively on projects initiated by others.
Experience with infrastructure automation and distributed-systems architecture, focused on building tools to manage large-scale private or public cloud platforms in production.
Experience with one or more of Python, Go, C/C++, or Java.
Comprehensive understanding of one or more of Linux, networking, storage, and container technologies.
Experience with public cloud, Infrastructure as Code, and Terraform.
Distributed-systems experience.

Additional Qualifications

Interest in crafting, analyzing, and troubleshooting large-scale distributed systems.
Systematic problem-solving approach, strong communication skills, ownership, and drive.
Ability to identify issues, improve code performance, and automate routine tasks.
Experience operating or handling large private and public cloud systems based on Kubernetes or Slurm.

Benefits

Equity and benefits are provided.
NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until November 14, 2026.