NVIDIACUDA Full Stack & AI Test Dev Intern - 2027
NVIDIA is hiring a CUDA Full Stack & AI Test Dev Intern - 2027 in Shanghai, China. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Python, Node.js and React.
- Level classifies it as an internship.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Develop LLM-powered features and full-stack web applications for CUDA test analysis, failure diagnosis, and engineering productivity as an intern.
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 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 interested in working with smart technical people across countries, this job is for you.
Our team mainly focuses on CUDA automation testing and CUDA test development. We build and own an internal full-stack web platform that CUDA engineers worldwide rely on to analyze automated test results, and we are now expanding it with LLM-powered AI features for CUDA test analysis, failure diagnosis, and AI application testing. We are looking for a Full Stack & AI Software Engineer Intern.
What you'll be doing:
Develop and maintain full-stack web applications for CUDA test analysis, including data-intensive dashboards, large-scale data grids, and visualization
Build front-end and back-end features using modern technologies such as React, Python/Node.js, databases, and APIs
Develop LLM-powered features for automated test analysis, failure diagnosis, and engineering productivity
Execute QA testing and test automation for NVIDIA ARM-based products and AI applications
What we need to see:
Pursuing MS or PhD degree from a leading university in computer science
Work 5 days a week for at least 1 year
Familiarity with modern full-stack development, including JavaScript frameworks, backend development, databases, and APIs, good Python scripting skills are a must
Understanding of LLM applications, AI agents, and AI application testing/evaluation
Good troubleshooting and problem-solving skills
Ways to stand out from the crowd:
Experience with automated testing and test frameworks such as Playwright or Vitest
Excellent English communication and collaboration skills
How we rate this
CUDA Full Stack & AI Test Dev Intern - 2027 at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where full stack development was part of your work. What did you do?
- Tell me about a project where llm application was part of your work. What did you do?
- Tell me about a project where test automation was part of your work. What did you do?
- Tell me about a project where failure diagnosis was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Full Stack Development, LLM Application, Test Automation, and Failure Diagnosis. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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