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Developer Technology Engineering Intern, AI - 2027

NVIDIA

Developer Technology Engineering Intern, AI - 2027

full-timePosted: Aug 26, 2026Updated: Aug 27, 2026Beijing, China

Job Description

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 architecturesYou will provide the best AI solutions using GPUs working directly with key customersCollaborate 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.

Locations

  • Beijing, China
  • Shanghai, China

Responsibilities

  • 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.
  • 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.

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