1 day ago
Munich, GermanyIntern
Responsibilities
- Research and develop techniques to GPU-accelerate applications in scientific computing, computational engineering, and data science.
- Perform in-depth analysis and optimization for current and next-generation GPU architectures.
- Work with application developers to design and optimize parallel algorithms and data structures using GPUs.
- Develop libraries and contribute directly to applications.
- Collaborate with architecture, research, libraries, tools, and system software teams on future architectures, software platforms, and programming models.
Requirements
- Pursuing an MSc or preferably PhD in an engineering, computer science, or related discipline.
- 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, organization, problem-solving, time-management, and prioritization skills.
- Domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful but not required.
Benefits
- Comprehensive benefits package.
- Internship pay is prorated for the duration of the internship.
- Expected annual rates are EUR 47,850–82,940 in Germany and EUR 40,500–70,200 in France.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.