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:
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- 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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