Image and Data Processing Libraries Intern
NVIDIA
Image and Data Processing Libraries Intern
NVIDIA
Designs the chips and software that power AI
Around the world, leading commercial and academic organizations are using GPU to redefine AI, scientific and engineering simulations, and data analytics. Did you know that the GPU accelerated libraries developed by NVIDIA are used in such industries such as healthcare, VR, autonomous vehicles, social media, and e-commerce? If the idea of contributing to these excite you, come join our team and help us build accelerated software libraries which are used by the entire world.
In this role you will be part of our team responsible for the development of libraries that provide groundbreaking functionality and performance. The internship may include extending the capabilities of existing as well as building new libraries that will be used in various AI and HPC applications. It will involve working with senior software engineers who will provide mentorship and guidance.
The project will include implementing new image and data processing algorithms, defining APIs, analyzing performance, finding appropriate solutions for difficult numerical corner cases, and other general software engineering work.
What you’ll be doing:
What we need to see:
Ways to stand out from the crowd:
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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.
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