Senior Software Quality Engineer

NVIDIA•Us, CA

About The Position

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people! Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world! What You'll Be Doing: Construct, enhance, and sustain automated test frameworks and pipelines for server firmware and software, ensuring exceptionally high standards. Build and optimize detailed test automation to expand coverage, efficiency, and reliability, with the goal of seamless execution. Develop OS/System-Level Automation and Test Automation software/scripting/etc. Use AI-powered tools to enable and implement CI/CD pipelines, optimize test execution, and drive scalable automation across workflows. Lead platform bring-up and integration, ensuring diagnostics are embedded early and effectively across the server lifecycle. Drive hardware validation strategy in collaboration with architecture and hardware teams, crafting robust validation plans for new server generations. Introduce new automation to improve code coverage and overall product quality; pinpoint gaps and support reaching near-100% automation objectives. Analyze logs and failures that may span Hardware (HW), Software (SW), and Firmware (FW) and propose debug and mitigation strategies.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
5+ years of hands-on experience in test development, firmware development, automation, or software engineering.
Proven experience architecting diagnostics for complex server systems, especially at the SW/HW interface.
Deep systems knowledge: x86/ARM architectures, Linux/Windows OS internals, firmware (UEFI/BIOS), BMC, and platform security.
Familiarity with Hardware/Software management (components/devices/peripherals, drivers, etc).
OS: Administration Linux and Windows, Networking, Security, Imaging (Baremetal, VM, etc).
Expertise in programming languages like Python, Bash, TCL, Perl, Powershell, JavaScript for tool development and automation.
Comprehensive experience in server firmware and associated testing methods.
Experience with AI coding tools (e.g., Cursor, Windsurf, GitHub Copilot, Antigravity) and integrating them with MCP to test workflows.
Passion for quality, automation, and innovation in a fast-paced, dynamic environment.

Nice To Haves

Experience driving diagnostics across rack-level or cluster-level deployments.
Virtualization, Windows Hyper-V, KVM, K8's, Containerization, etc.
Background in cloud-scale infrastructure and partner engagement.
Experience with PyTest or related testing frameworks.
Experience in developing modern Software Verification Systems.

Responsibilities

Construct, enhance, and sustain automated test frameworks and pipelines for server firmware and software, ensuring exceptionally high standards.
Build and optimize detailed test automation to expand coverage, efficiency, and reliability, with the goal of seamless execution.
Develop OS/System-Level Automation and Test Automation software/scripting/etc.
Use AI-powered tools to enable and implement CI/CD pipelines, optimize test execution, and drive scalable automation across workflows.
Lead platform bring-up and integration, ensuring diagnostics are embedded early and effectively across the server lifecycle.
Drive hardware validation strategy in collaboration with architecture and hardware teams, crafting robust validation plans for new server generations.
Introduce new automation to improve code coverage and overall product quality; pinpoint gaps and support reaching near-100% automation objectives.
Analyze logs and failures that may span Hardware (HW), Software (SW), and Firmware (FW) and propose debug and mitigation strategies.