NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams with the smartest people in the world. Join us at the forefront of technological advancement.We are looking for software engineering interns for our BLAS and Linear Algebra teams which are a key part of high-performance computing and deep learning software stacks. The main purpose of these libraries is to provide the fastest computing primitives for sparse and dense linear algebra, like Cholesky decomposition and sparse and dense matrix products among many others. We see strong interest in optimization of such key functionalities from various industrial and research organizations - from Gaming and Machine Learning to autonomous driving and chip modeling. Some of these kernels spend several milliseconds while others involve hundreds of GPUs and spend hours. All of them need to be optimized for current and future GPUs that involve mathematical changes of algorithms. Does the idea of being at the heart of these projects and apply your knowledge to develop and optimize algorithms which make an impact around world excite you? If yes, then come and join our team! During your internship, you will work with senior software engineers on the libraries team who will provide mentorship and guide you in developing highly optimized algorithms. 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:Prototype and develop numerical algorithms for high-performance math libraries in the areas of dense and sparse linear algebra for single node and multi GPU clustersAnalyze the performance of GPU or CPU implementations and find opportunities for improvements.Collaborate with team members to understand software use cases and requirementsWhat we need to see:Studying towards a MS or PhD degree in Computer Science, Applied Math, Engineering, or related field.Strong C++ programming, debugging, performance analysis, and test design skills.Experience implementing sparse or dense linear algebra algorithms.Parallel programming experience using CUDA, multi-threading or MPI.Ways to stand out from the crowd:Exposure to floating-point arithmetic and numerical error analysis.A scripting language, preferably Python.NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you!The hourly rate for our interns is $19 - $93. Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.You will also be eligible for Intern benefits.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning
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