GPU Compute DevTech Intern - HPC & Parallel Computing

NVIDIA Corporation; Zürich; Hybrid; CHF 100,000 - 140,000; Full time

Job summary

NVIDIA Corporation seeks a highly capable MSc/PhD candidate to advance GPU-accelerated techniques for HPC applications. You will analyze performance and optimize for current and future GPU architectures, collaborating with architecture, research, and software teams.

Strong skills in C/C++ (and Fortran) and parallel programming, plus CUDA C/C++ and OpenACC, are required, with solid math basics and problem-solving ability.

Qualifications

• Pursuing a MSc or preferably PhD in engineering or computer science.
• Domain knowledge in telecommunications, medical imaging, machine learning, or natural sciences is helpful.
• Strong mathematical fundamentals and programming skills.

Responsibilities

• Research and develop GPU-accelerated techniques for high-performance computing applications.
• Analyze and optimize performance on current and next-generation GPU architectures.
• Collaborate with architecture, research, libraries, tools, and system software teams to influence designs.

Skills

C/C++

Fortran

Parallel programming

CUDA C/C++

OpenACC

Linear algebra

Education

MSc or PhD in engineering or computer science

Tools

CUDA

OpenACC

Job description

NVIDIA Corporation seeks a highly capable MSc/PhD candidate to advance GPU-accelerated techniques for HPC applications. You will analyze performance and optimize for current and future GPU architectures, collaborating with architecture, research, and software teams.

Strong skills in C/C++ (and Fortran) and parallel programming, plus CUDA C/C++ and OpenACC, are required, with solid math basics and problem-solving ability.