Principal Software Engineer

Nvidia

Confirmed live yesterday Trusted

Remote

Quick summary

Work type: Remote
Location: Seattle, WASanta Clara, CA
Employment: Full-time
Posted: 81 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $195k

$131k $253k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $169,550–$219,543.

Based on 240 similar postings.

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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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer

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As a Principal Software Engineer for DGX Cloud, you will join the DSX Kubernetes Fleet team to build and manage a massive GPU accelerated container platform. You will design and develop software to manage a fleet of Kubernetes clusters for GPUs and DPUs, focusing on automation, lifecycle management, and deployment safety. Your daily work involves building APIs and workflows that turn high-level deployment intent into production-ready AI infrastructure management, including provisioning, upgrades, and decommissioning. You will utilize Go, C, and Unix/Linux kernel internals while leveraging Kubernetes, container technology, and distributed software design. The role requires expertise in systems programming, data structures, and algorithms to solve complex problems regarding performance, security, and reliability for AI Factory scale infrastructure, while automating build, test, and release processes for cloud-native applications.

What does a Software Engineer earn in Washington?

Median $202800 from 409 postings across 38 companies.

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Skills

Kubernetes Go C Linux Cloud Computing CI/CD Gitlab Argo Flux Container Orchestration Distributed Systems Unix Data Structures and Algorithms GPU DPU Confidential Computing

What you'll do

Design and develop software for managing a fleet of Kubernetes clusters for GPUs and DPUs.
Build APIs and workflows to turn high-level deployment intent into production-ready AI infrastructure.
Manage the full lifecycle of AI Factory Kubernetes clusters from provisioning through decommissioning.
Automate and optimize build, test, integration, and release processes for cloud-native applications.
Improve NVIDIA accelerators within the Kubernetes environment using Cloud Native technologies.
Develop software to simplify the development, deployment, and monitoring of GPU and DPU accelerated applications.
Ensure seamless integration of software by collaborating with various engineering teams across the company.

What we're looking for

BS/MS in Computer Science or related field or equivalent experience.
15+ years of proven work experience in large scale environments.
Expert-level knowledge in systems programming languages like Go and C with a solid grasp of Data Structures and Algorithms.
Strong understanding of Container Orchestration Systems (Kubernetes) and Container Technology.
In-depth knowledge and experience with Unix/Unix-like kernel internals, particularly Linux.
Hands-on automation experience with modern infrastructure tools and technologies.
Proven experience in setting up, maintaining, and automating continuous deployment systems.
Strong background in Cloud Computing and Distributed Software design and development.