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 Software QA Development Engineer; you will collaborate with multi-functional groups. SWQA 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 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 plus equivalent with 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.

• Solid experience with AI development tools, including creating test cases, automating test cases, and ensuring comprehensive code coverage, among other related tasks

• 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