Senior SWQA Test Development Engineer - NIM

Posted 3 Days Ago
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Santa Clara, CA
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
As a Senior Software QA Test Development Engineer, you will develop test plans, execute tests, automate test cases, and report bugs. Your responsibilities include managing bug lifecycles, collaborating with teams, and ensuring product quality through innovative testing strategies.
Summary Generated by Built In

NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you.

We are now looking for a Senior Software QA Test Development Engineer, you will collaborate with multi-functional groups. SWQA test developer engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA engineer can improve productivity or optimize test plan. As a SWQA test developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products.

What you’ll be doing:

  • Review product requirements and develop test matrix.

  • Build test plan, design test case, execute and report test progress, bugs, and results to management.

  • Automate test cases and assist in the architecture, crafting and implementing of test frameworks.

  • Manage bug lifecycle and co-work with inter-groups to drive for solutions.

  • In-house repro and verify customer issues/fixes.

What we need to see:

  • BS or higher degree or equivalent experience in CS/EE/CE

  • 5+ years QA experience.

  • Proficient in Unix/Linux and shell/python programming skills.

  • Rich experience in test cases development, tests automation in API/UI and failure analysis.

  • Good knowledge and hands-on experience in model testing and LLM benchmarking

  • Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc.

  • Excellent communicator, fluent written and verbal English.

  • Good teamwork with ability to work independently.

  • Passion to learn new hardcore technology.

Ways to stand out from the crowd:

  • Experience working with NVIDIA GPU hardware is a strong plus

  • Background in deep learning frameworks is a plus

  • Experience in parallel programming ideally CUDA/OpenCL is a plus

The base salary range is 132,000 USD - 258,750 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.

Top Skills

Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
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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