NVIDIADeveloper Technology Engineering Intern, AI - 2027
NVIDIA is hiring a Developer Technology Engineering Intern, AI - 2027 in Beijing, China. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions CUDA, C and Fortran among its tools and skills.
- Level classes it as an internship.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Develop state-of-the-art deep learning and GPU optimization techniques as an AI Developer Technology Engineering Intern.
Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films.
Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as an AI Developer Technology Engineering Intern.
What you will be doing:
Work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures
You will provide the best AI solutions using GPUs working directly with key customers
Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models.
What we need to see:
Pursuing MS, or PhD degree from a leading university in an engineering or computer science related field.
Programming proficiency in C/C++ and/or Fortran with a deep understanding of software design, programming techniques, and algorithms.
Strong knowledge of C/C++, software design, programming technique and AI algorithms.
Experience with parallel programming, ideally CUDA C/C++.
Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.
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) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
How we rate this
Developer Technology Engineering Intern, AI - 2027 at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What have you built with speech recognition or text-to-speech, and where did it break?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where gpu optimization was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer vision, Speech, Deep learning, Machine learning, and GPU Optimization. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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