Deep Learning Software Engineering Intern, Test Development - 2027
At a glance
Junior Machine Learning Engineering role at NVIDIA. China, Shanghai · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and refine automated tests for deep learning software, including cuDNN, TensorRT and optimized frameworks
- Check functionality, compatibility and performance as deep learning software releases move through testing
- Work with developers to investigate defects, confirm corrections and add tests or strengthen test plans
- Apply AI tools to generate test materials, spot defects, fix bugs and support daily work
What you bring
- You are pursuing a master's degree or higher in computer science, electrical engineering or computer engineering
- You can script in Python, Perl or Bash and work in Linux
- You have experience with AI tools and can communicate fluently in spoken and written English
Who this fits
This full-time internship suits someone pursuing graduate study who wants hands-on software testing and test automation work. Familiarity with a deep learning framework is a plus; C or C++ experience, NVIDIA GPU hardware, CUDA, and a record of using AI tools to improve workflows can strengthen your fit.
From the employer
Deep Learning SWQA Mobile team has permission to open 1 intern Req. Looking for full time interns to help on cuDNN, TensorRT, DL FW, TensorRT Model Connect or DL Mobile SWQA projects in the next 12+ months.
We are now looking for a Deep Learning Software Test Development Engineering 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 Deep Learning Software products, such as cuDNN, TensorRT, NVIDIA optimized Frameworks (E.g. TensorFlow, PyTorch, MxNET, etc.)
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.
Utilize AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, CBTP, bug fixing and day to day assistance.
What we need to see:
Pursuing MS or higher degree in CS/EE/CE.
Scripting language (Python, Perl, bash), Linux knowledge is required.
Experiences in C/C++ programming is a plus.
Familiarity any Deep Learning Framework is a strong plus.
Good communication skills, fluent oral and written English.
Experience with AI tools.
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.
Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.