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NVIDIA

Designs the chips and software that power AI

Developer Technology Engineering Intern - Compute Performance

Software EngineeringConfirmed live in the last 24 hours
Internship€19.47 - €39.88 /hrIn-person

About the Job

Requirements

  • Pursuing a Master of Science degree, with a PhD preferred, in an engineering or computer-science-related discipline.
  • 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, a logical approach to problem solving, good time management, and task prioritization skills.

Responsibilities

  • Research and develop techniques to GPU-accelerate leading applications in high-performance computing, including scientific computing, computational engineering, and data science.
  • Analyze and optimize applications in depth to maximize performance on current and next-generation GPU architectures.
  • Work directly with application developers to understand their current and future problems, and craft and optimize core parallel algorithms and data structures for GPU solutions through library development and direct contributions to applications.
  • Collaborate with architecture, research, libraries, tools, and system software teams to influence next-generation architectures, software platforms, and programming models by investigating effects on application performance and developer productivity.

Desired Qualifications

  • Domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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