We’re working on the next generation of recommendation tools and pushing the boundaries of accelerating model training and inference on GPU. You’ll join a team of ML, HPC and Software Engineers and Applied Researcher developing a framework designed to make the productization of GPU-based recommender systems as simple and fast as possible.

What you’ll be doing :

• In your role as CUDA Engineer Intern you will be profiling and investigating the performance of optimized code together within our HPC team.

• Part of this job will be to perform tests, unit tests and validate the numerical performance and correctness of the code.

• You will discuss your approach and results together with our CUDA engineers.

What we need to see:

• Experience with c++, CUDA, python and Linux.

• Bachelor or Master degree in software engineering or technical field such as mathematics or applied science.

• Communication skills

• Ambitious to grow and learn about building machine learning applications, optimization and software engineering.

  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 forward-thinking 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.

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