Deep Learning Software QA Engineer Intern
NVIDIA
Deep Learning Software QA Engineer Intern
NVIDIA
Designs the chips and software that power AI
We are now looking for a Deep Learning Software QA 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:
GPU Software testing and test automation improvement for NVIDIA optimized Deep Learning Frameworks (E.g. TensorFlow, PyTorch, PyG, etc.) and workloading running on GPU (E.g. SPARK RAPIDS, TAO, etc.)
Maintain & develop test automation infrastructure (web based).
Be responsible for functionality, compatibility, and performance tests in DL SW stack release.
Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans.
Web service developing
What we need to see:
Pursuing Master or higher degree in CS/EE/CE (Graduation in CY2028).
Direct Spark ETL and AI Agent experience.
Good user/development experience of virtualization like VM & Docker container & k8s & Slurm.
Good python skillset, know Flask, Linux knowledge is required.
Experiences in C/C++/Java programming is a plus.
Familiarity any Deep Learning Framework is a strong plus.
Good communication skills, fluent oral and written English.
Ways to stand out from the crowd:
Familiarity working with NVIDIA GPU hardware is a strong plus.
Background with NVIDIA GPU Computing (CUDA) is a strong plus.
Development experience in using AI tools/Agent for E2E workflow or project features
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 Infrastructure team, and help build the real-time, cost-effective computing platform driving our success in the exciting and quickly growing field of AI.
NVIDIA 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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