CUDA Math Libraries Intern

NVIDIA is looking for a software engineering intern for its mathematical libraries team. Researchers and companies around the world are using GPUs to redefine areas such as artificial intelligence, deep learning, engineering, and scientific computing. Did you know that the GPU accelerated libraries developed by NVIDIA are used in various industries such as: healthcare, VR, autonomous vehicles, social media, and e-commerce? NVIDIA also recently announced Grace CPU and Grace Hopper Superchips that will further accelerate computing. 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 top performance and functionality. Your contributions may include extending the capabilities of existing libraries as well as building new libraries that will be used in various AI and HPC applications. Interacting and collaborating with engineers within your team as well as internal partners is essential to this role. This internship involves working with senior software engineers who will provide mentorship and guidance. Projects will involve implementing new numerical algorithms, defining APIs, analyzing performance, finding appropriate solutions for difficult numerical corner cases, and other general software engineering work.What you’ll be doing:Collaborating with team members and other teams to understand software use cases and requirements.Research, analyze, and document state-of-the art algorithmsDevelop algorithms for image processing, image and data encoding/decoding or high-performance computing (HPC)Analyze and improve performance of existing implementationsWhat we need to see:Pursuing a degree in Computer Science, Artificial Intelligence, Applied Math, or related fieldAlgorithms, mathematical fundamentalsProgramming skills (C/C++, Python), debugging, performance analysis, and test design skillsAbility to work independently and manage your own development effortGood communication and documentation habitsTechnical writing skillsWays to stand out from the crowd:Knowledge of CPU or GPU hardware architectureGPU programming experience (CUDA or OpenCL)Knowledge of image encoding and decoding algorithms for JPEG, JPEG2000, TIFF or PNG formatsKnowledge of data compression and decompression algorithmsNVIDIA 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!