Senior AI Infrastructure Engineer - DGX Cloud

Nvidia

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $152,000–$241,500 / yr
Posted: 2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $197k

$139k most similar roles pay here $274k

This role pays less than 60% of similar roles. Most pay $167,187–$246,150 — the shaded band above. At the midpoint, this role pays about $197k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 985 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 971 roles with salary data.

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At a glance

TL;DR · Senior AI Infrastructure Engineer - DGX Cloud

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NVIDIA’s DGX Cloud group seeks a Senior AI Infrastructure Engineer to design, build, and maintain large-scale production systems for AI training and inferencing platforms. This role involves deploying internal tooling, conducting performance analysis on multi-GPU clusters, and supporting services throughout their lifecycle. The engineer will ensure system reliability through automation, capacity management, and continuous improvement, participating in an on-call rotation to handle production issues. Ideal candidates have a BS degree or equivalent experience in computer science or related fields, with 5+ years of hands-on experience in infrastructure automation, distributed systems architecture, and cloud technologies like Kubernetes and Terraform. Proficiency in Python, Go, C/C++, Java, Linux, networking, storage, and containers is essential, along with a passion for large-scale system management and performance optimization.

Skills

Python Go Kubernetes Terraform Docker Linux Networking Storage CI/CD PostgreSQL MySQL Prometheus Grafana Slurm AWS Azure Google Cloud Platform Git Jenkins Ansible Nginx Redis MongoDB

What you'll do

Design and deploy internal tooling for large-scale AI training and inferencing platforms.
Conduct performance analysis on multi-GPU and multi-node clusters.
Engage in the full lifecycle of services including design, deployment, and operation.
Maintain system health by monitoring availability and latency post-deployment.
Scale systems sustainably through automation to enhance reliability and velocity.
Participate in an on-call rotation for production system support.

What we're looking for

5+ years of experience in infrastructure automation and distributed systems.
BS degree in Computer Science or related technical field with coding emphasis.
Experience with Linux, networking, storage, containers, and public cloud technologies.
Proficiency in Python, Go, C/C++, Java for building large-scale production tools.
Expertise in Kubernetes, Terraform, and Infrastructure as Code (IAAC) practices.
Capability to design, deploy, and maintain high-performance AI training platforms.