We are looking for a Senior Software QA engineer in NVIDIA’s Deep Learning SWQA team.

The position is in NVIDIA Deep learning software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms.

You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world!

What you’ll be doing:

• As a Software QA Engineer who is engaged in the success of this team and company, you will devote time to process definition and improvement, come up with creative solutions to challenging problems to help us achieve our goals more efficiently.
• GPU testing for Nvidia Deep Learning Software products to ensure functionality, compatibility and performance for various SDK (cuDNN, TensorRT, etc) and Frameworks.
• Be responsible for Deep Learning Software features' test development and enhancement (Driver, SDK, and Frameworks).
• Work with development teams to triage issues, do root cause analysis, verify fixes, define new tests, improve test plans.

What we need to see:

• BS or higher degree in CS/EE/CE or equivalent.
• 5+ years of software quality assurance or test automation background with knowledge of test infrastructure and strong analysis skills.
• Scripting language (Python, Perl, Bash) knowledge and UNIX/Linux experience.
• Good C/C++ software development or test development experience.
• Excellent English written and oral communication skills.
• Able to juggle conflicting/changing priorities and maintain a positive attitude while experiencing challenging and dynamic schedules.

Ways to stand out from the crowd:

• Familiarity with NVIDIA GPU hardware products.
• Understanding and working knowledge with any Deep Learning Framework.
• Working knowledge of NVIDIA GPU Computing (CUDA) and CUDA libraries for Deep Learning.
• Experience in VectorCAST, Bullseye, Gcov, or Coverity tools.
• Automation experience.