Nvidia Quality Assurance Engineer 

United States, California 

933478231

What you’ll be doing:

As a Quality Assurance Engineer, you will take part of testing the latest GeForce drivers so it aligns with the highest standards of quality and functionality. In this role you can expect to:

• Test several popular and unreleased games to make sure the latest GPU driver features are implemented and supported.

• Complete comprehensive check lists of tests with realistic customer scenarios and detail their behavior.

• Debug issues to identify the root cause and participate in post-mortem analysis along with peers and senior team members.

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

• Test execution and test plan development while sending out weekly status reports to partners and notifying of any major issues.

• Optimally estimate and prioritize tasks to build a realistic delivery schedule.

• Build innovative ways to automate and expand our software testing

What we need to see:

• Associates Degree or Bachelors Degree (or equivalent experience).

• 5+ years of validated experience.

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

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

• Excellent written and verbal communication skills to articulate quality of products.

• We want you to command presence and the technical and leadership skills to speak up on major issues prior to product release.

• The ability to work with a team of engineers in a fast-paced environment.

• You can configure and build high end gaming PCs.

Ways to stand out from the crowd:

• A degree in ComputerScience/IT/Electronicsengineering.

• Experience with GeForce technologies like DLSS and Reflex.

• Able to participate in tournaments and not letting it affect your job as a QA engineer and be a top finisher in outstanding tournaments.

• Programming experience in C#, .Net & Python and applying Object-Oriented Programming concepts.

• Background with working on projects that use Machine Learning/Deep Learning.