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NVIDIA

Software Test Developer - Graphics

Sorry, this job was removed at 07:19 p.m. (PST) on Monday, Jun 02, 2025
In-Office or Remote
6 Locations
In-Office or Remote
6 Locations

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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. We are looking for a Software Engineer to work on compiler testing and compiler performance testing for the compiler graphics verification team. You will be helping us to drive better performance and deliver a state of the art compiler for graphics.

What you’ll be doing:

  • Develop and review test plans, implement test cases, automate tests with NVIDIA test frameworks, and author test reports.

  • Analyze performance degradation or functional defects in compilers, identify regression root cause, and perform reviews to continuously improve test coverage.

  • Use test suites to find, report and track compiler performance changes. Work with development team to drive regressions to resolution. Generate statistics based on performance data, identify and investigate outliers and monitor performance trends. Maintain historical data and baselines for comparison.

  • Collaborate with multi-functional teams including compiler developers, driver developers, hardware architects to ensure smooth integration and performance of our graphics features, and assist in providing automated solutions for testing.

  • Help to identify potential or observed weaknesses current processes, offer ideas for actions that can improve the current process, and participate in quality initiatives and drive continuous improvement.

What we need to see:

  • Bachelor’s, Master’s Degree in Computer Science or equivalent experience.

  • Proficiency in programming languages such as Python, C/C++ and/or C#

  • 2+ years experience with writing test plans, test development, test automation, test execution and reporting in a production environment.

  • Deep understanding of Software Development Life Cycle (SDLC), and Software Testing Methodologies.

  • Comfortable working collaboratively with team members from diverse geographic locations.

  • Excellent communications skills, self-motivated and well organized.

  • You should be focused, learn quickly, be productive under tight schedules, and have strong analytical skills with attention to detail.

  • Proven capability in problem solving and implement solutions.

  • Strong troubleshooting and debugging skills.

  • Demonstrated uses of creative thinking for solutions to exciting problems that matter.

Ways to stand out from the crowd:

  • Experience with modern GPU graphics APIs: DirectX, Vulkan, HLSL/GLSL.

  • Proficient industry experience in testing production software. Preferably compiler or other system software.

  • Previous compiler development and/or compiler verification/test or performance analysis experience.

  • Familiarity with statistical analysis tools for identifying and isolating out-of-bound behavior.

  • Experience with revision control software and management tools, such as Git, Perforce, JIRA, Confluence and Make.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

The base salary range is 108,000 USD - 212,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

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