Deep Learning Software Engineer Intern
NVIDIA
Deep Learning Software Engineer Intern
NVIDIA
Designs the chips and software that power AI
We are now looking for a Deep Learning Software Test Development Engineer Intern!
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:
Be responsible for functionality, compatibility, and performance tests in NVIDIA AI SW stack release.
Develop, maintain, and improve test automation infrastructure with using AI tools. Use AI to improve quality and productivity across QA End-to-End workflow.
Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans.
What we need to see:
Pursuing MS or higher degree in CS/EE/CE or a related field.
Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation.
Good python, C++ programming skillset, Linux knowledge is required.
Experience in software development with popular AI models is a strong plus.
Good communication skills, fluent oral and written English.
Ways to stand out from the crowd:
Be familiar with deep neural network training, inference, optimization in typical DL Frameworks.
Background with NVIDIA GPU Computing (CUDA) is a strong plus.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you. Come, join our AI Software QA Test development team, and help build the real-time, cost-effective computing platform driving our success in the exciting and quickly growing field of AI.
#deeplearningNVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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