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Developer Technology Engineering Intern - Compute Performance

NVIDIA

locationZurich

Posted 17 days ago

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  • Level

    Entry level

  • Employment

    Fulltime

  • Field

    Backend

  • Workplace

    On-site in Zurich

  • Apply

    On the company site

  • Open until

    14 Dec 2026

  • Skills

    CUDA, C++

NVIDIA is hiring passionate, world-class computer science studetns to work in its Compute Developer Technology (Devtech) team. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and talented people in the world working with us and our engineering teams are growing fast in some of the hottest and state of the art fields: Deep Learning, Artificial Intelligence, Autonomous Vehicles, Supercomputing and more. Are you a creative and autonomous computer scientist with a real passion for parallel computing? If so, we want to hear from you.

What you will be doing

In this role, you will research and develop techniques to GPU-accelerate leading applications in high performance computing fields within scientific computing, computational engineering, and data science. You will be performing in-depth analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures. This involves:

  • Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications.
  • Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models, by investigating the impact on application performance and developer productivity.

What we need to see

  • Pursuing a MSc or preferably PhD degree in an engineering or computer science related discipline. While not a requirement, domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful.
  • Programming fluency in C/C++ and/or Fortran with a deep understanding of software design, programming techniques, and algorithms.
  • Strong mathematical fundamentals, including linear algebra and numerical methods.
  • Experience with parallel programming, ideally CUDA C/C++ and OpenACC.
  • Strong 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.​

CUDAC++

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Frequently asked questions

Quick answers about this role at NVIDIA.

Where is the Developer Technology Engineering Intern - Compute Performance position at NVIDIA located?

The role is based in Zurich, Switzerland.

What is the salary for this Developer Technology Engineering Intern - Compute Performance role?

NVIDIA has not published a salary range for this position. Techify shows ranges whenever the employer provides them.

What type of employment and seniority is this?

It is a fulltime position at entry level level.

Which skills and technologies are relevant for this Developer Technology Engineering Intern - Compute Performance job?

The posting highlights CUDA, C++.

How do I apply for the Developer Technology Engineering Intern - Compute Performance job at NVIDIA?

This listing comes from the employer's careers site. Use the Apply button to open the original posting and apply directly with NVIDIA.

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