Senior Software Engineer - BaseOS

Reposted Yesterday
Hiring Remotely in Santa Clara, CA, USA
In-Office or Remote
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and build CI/CD pipelines, develop testing frameworks, implement infrastructure as code, and champion automation initiatives for NVIDIA's platforms.
Summary Generated by Built In

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company, and build our teams with the smartest people in the world. Join us at the forefront of technological advancement.

NVIDIA BaseOS is the Linux distribution for NVIDIA GPU-based platforms deployed in AI and Data-Analytics industries. As a Senior Infrastructure Engineer, you'll design and build robust CI/CD pipelines, champion automation initiatives, and develop comprehensive testing frameworks. Working closely with System and Software development teams, you'll drive end-to-end automation for all developer and release workflows.

What You'll Be Doing:

  • Design, implement, and maintain CI/CD pipelines for building OS images across Ubuntu and RHEL distributions

  • Build unit testing and integration testing frameworks using Go and Python

  • Optimize CI/CD infrastructure using Jenkins and GitlabCI

  • Implement infrastructure as code with Terraform and work with Kubevirt for virtualized workloads

  • Create and maintain Ubuntu and RHEL packaging solutions (deb/rpm)

  • Identify infrastructure improvements and implement metrics gathering systems for KPIs and dashboards

  • Champion automation initiatives to achieve 100% end-to-end automation across developer and release workflows

What We Need to See:

  • 5+ years of software engineering experience focused on infrastructure and platform systems

  • Expert-level proficiency in Go and Python

  • Strong experience with Jenkins, GitlabCI, and Terraform

  • Hands-on experience with Kubevirt and Ubuntu/RHEL packaging (deb/rpm)

  • Proven unit testing strategies and framework development experience

  • Expertise in KPI Infrastructure for metrics identification, gathering, and dashboards

  • Experience using AI tools such as Cursor/Claude

  • Bachelor's degree in Computer Science, Engineering, or equivalent experience

Ways to Stand Out From the Crowd:

  • Functional testing and end-to-end test automation experience

  • Contributions to open-source infrastructure or Linux distribution projects

  • Experience with container orchestration and cloud-native technologies

If you're excited about building world-class infrastructure and automation systems that power NVIDIA's AI platforms, we'd love to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 9, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Gitlabci
Go
Jenkins
Kubevirt
Python
Rhel
Terraform
Ubuntu
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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