Senior CUDA Test Development Software Engineer, SDET

Reposted 5 Days Ago
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Shanghai, Shanghai Municipality, Shanghai
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and implement tests for CUDA driver and library, automate tests, improve coverage, and triage results in this senior engineering role.
Summary Generated by Built In

NVIDIA is the world leader in GPU Computing. We are passionate about four markets: Gaming, Automotive, Enterprise Graphics and HPC/Cloud Datacenters; in addition to our traditional OEM business. We are well positioned as the ‘AI Computing Company’, and our GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, big data, modern data centers, smart cities, and driving autonomous vehicles. We have some of the most brilliant and talented people in the world working for us. If you are talented, bright, driven and if working with smart technical people across countries sounds interesting, this job is for you. Our team is mainly focusing on CUDA automation testing, CUDA Safety and CUDA test development areas, and we are now looking for a Senior CUDA Test Development Software Engineer.

What you’ll be doing:

  • Design and Implement unit, integration, and API tests for CUDA driver and library

  • Design and implement tests for new features of CUDA driver and library

  • Automate CUDA tests, design test plan and enable them in automation testing infrastructure

  • Triage test results, isolate test failures and improve test coverage

What we need to see:

  • MS or PhD degree from a leading university in computer science or relevant

  • 3 years work experience at minimum

  • Strong programming and debugging skills with C/C++, Python and Makefile

  • Developer background who has experience using AI tool to automate QA end-to-end workflow

  • Rich experience in test cases development, tests automation and failure analysis

  • Good QA sense, knowledge, and experience in software testing

  • Strong Linux/Windows OS knowledge

Ways to stand out from the crowd:

  • Excellent English communication and collaboration skills

  • Experience in parallel programming, ideally CUDA, is a plus

  • Background in VectorCAST, Bullyseye, Gcov or Coverity is a plus

Top Skills

Bullseye
C/C++
Coverity
Cuda
Gcov
Linux
Makefile
Python
Vectorcast
Windows
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The Company
HQ: Santa Clara, CA
21,960 Employees
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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