Developer Technology Engineering Intern – Compute Performance

NVIDIA

. Research and develop techniques to GPU-accelerate leading applications in high performance computing fields within scientific computing, computational engineering, and data science .

Posted 9/30/2026internshipZurich • SwitzerlandEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in GPU acceleration techniques and parallel programming, with a strong foundation in C/C++ and Fortran. Capable of optimizing algorithms and data structures while collaborating effectively with cross-functional teams in high performance computing.

Highest-signal resume keywords

GPU Acceleration TechniquesC/C++ ProgrammingParallel Programming (CUDA C/C++ and OpenACC)Mathematical Fundamentals (Linear Algebra and Numerical Methods)Software Design and Algorithms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C/C++ ProgrammingFortran ProgrammingGPU Acceleration TechniquesParallel Programming (CUDA C/C++ and OpenACC)Software DesignAlgorithmsMathematical FundamentalsNumerical MethodsData StructuresPerformance Optimization

Soft Skills

Strong Communication SkillsOrganization SkillsLogical Problem SolvingTime ManagementTask Prioritization

Tools & Technologies

NVIDIA LibrariesNVIDIA ToolsNVIDIA System Software

Industry Keywords

High Performance ComputingScientific ComputingComputational EngineeringData ScienceMachine LearningDeep LearningTelecommunicationsMedical ImagingNatural Sciences

Tech Stack

Tools & technologies

C++

About the role

Key responsibilities & impact

Research and develop techniques to GPU-accelerate leading applications in high performance computing fields within scientific computing, computational engineering, and data science
Perform in-depth analysis and optimization for current and next-generation GPU architectures
Work directly with key application developers to understand current and future problems
Craft and optimize core parallel algorithms and data structures using GPUs
Contribute through library development and direct application contributions
Collaborate with NVIDIA architecture, research, libraries, tools, and system software teams
Investigate impacts on application performance and developer productivity to influence next-generation architectures, software platforms, and programming models

Requirements

What you’ll need

Pursuing an MSc or preferably PhD degree in an engineering or computer science related discipline
Domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful, but not required
Programming fluency in C/C++ and/or Fortran
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
Logical approach to problem solving
Good time management and task prioritization skills

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Equal opportunity employment practices