Quality Assurance Software Developer Engineer in Test, GeForce GPU

NVIDIA AI

📍Santa Clara, CA
Posted May 23, 2026

Job Overview

Position

Quality Assurance Software Developer Engineer in Test, GeForce GPU

Company

NVIDIA AI

Location

Santa Clara, CA

Work Type

On-site

Job ID

li-4414394594

Job Description

Job Requisition ID

JR2011328

Job Category

Engineering

Time Type

Full time

Are you passionate about inspiring change, building data driven tools to improve software quality, and ensuring customers have the best experience? If so, we have a phenomenal opportunity for you! NVIDIA is seeking a creative, and hands-on software engineer with a test to failure approach who is a quick learner, can understand software and hardware specifications, build reliable tests and tools C++/C#/Python to improve quality and accelerate delivery of GeForce NVIDIA products. The successful candidate will demonstrate substantial experience with AI technologies for automation of test cases, as well as an in-depth understanding of both Windows and Linux operating systems.

What You’ll Be Doing
As a Software Development Engineer in Test, you will take part in technical design and implementation of tests for NVIDIA software products with the goal to identify defects early in the software development lifecycle. You will also build tools that accelerate execution workflows for the organization. In this role you can expect to:

  • Design and implement automated tests incorporating AI technologies for NVIDIA's device driver software and SDKs on various Windows and Linux operating systems.

  • Develop automated end to end tests for NVIDIA device driver and SDKs on windows platform. Execute manual and automated tests, identify, and report defects. Measure code coverage, analyze and drive code coverage improvements.

  • Develop applications and tools that bring data driven insights to development and test workflows.

  • Build tools/utility/framework in Python / C / C++ which would help automate and optimize the testing workflows in GPU domain.

  • Write maintainable, reliable, and well detailed code. Debug issues to identify the root cause. Provide peer code reviews including feedback on performance, scalability, and correctness

  • Optimally estimate and prioritize tasks in order to create a realistic delivery schedule and work on challenging technical and process issues.

  • Generate and test compatibility across a range of products and interfaces.

  • Work closely with leadership to report progress by generating effective and impactful reports

What We Need To See

  • B.E./B. Tech degree in Computer Science/IT/Electronics engineering with strong academics or equivalent experience

  • 5+ years of programming experience in Python/C/C++ with experience in applying Object-Oriented Programming concepts.

  • Hands-on knowledge of developing Python scripts with application development concepts like dictionaries, tuples, RegEx, PIP etc.

  • Good experience with using AI development tools for test plans creation, test cases development and test cases automation

  • Experience with testing RESTful APIs and the ability to conduct performance and load testing to ensure the application can handle high traffic and usage.

  • Experience working with databases and storage technologies like SQL and Elasticsearch

  • Good understanding of OS fundamentals, PC Hardware and troubleshooting.

  • Skillful at debugging issues and have experience using debugging tools like WinDBG/gdb

  • Working knowledge of GPUs devices and technologies like DLSS, Frame Generation, Reflex, CUDA, G-Sync, etc.

  • The ability to collaborate with multiple development teams to gain knowledge and improve test code coverage

Ways To Stand Out From The Crowd

  • Prior project experience with building ML and DL based applications would be a plus

  • Good understanding of testing fundamentals

  • Good problem solving skills (solid logic to apply in isolation and regression of issues found).

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 26, 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.

Interview Prep

AI-powered insights to help you prepare

Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How have you leveraged AI technologies to automate test case creation and execution in your previous projects, and how would you apply that to testing NVIDIA's GeForce device drivers?
  • 2.Walk me through your process for debugging a critical crash in a NVIDIA GPU driver on a Windows platform using WinDBG.
  • 3.How would you design a performance and load testing strategy for RESTful APIs that serve data-driven insights to development workflows?
🎯Behavioral Questions (3)
  • 1.Tell me about a time you had to learn a complex hardware or software specification quickly to build a reliable test. How did you ensure your test was accurate?
  • 2.Describe a situation where you identified a defect early in the software development lifecycle that others missed. What was the impact?
  • 3.Give an example of a time you had to optimally estimate and prioritize testing tasks to create a realistic delivery schedule under pressure.
🧩Situational Questions (2)
  • 1.You are tasked with improving code coverage for an NVIDIA SDK, but the current tests only cover basic happy paths. How do you approach driving code coverage improvements?
  • 2.A newly released automated end-to-end test suite for a Windows device driver is intermittently failing, causing noise in the regression reports. How do you handle this?

Resume Keywords

Make sure these keywords appear on your resume

SDETPythonC++AI Test AutomationGPU TestingCUDAWinDBGLinuxRESTful APIsCode CoverageElasticsearchDriver Validation

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