Machine Learning Engineering Intern

As a deep learning library performance software engineer, you will be developing optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs. Writing highly tuned compute kernels, mostly in C++ CUDA, to perform core deep learning operations (e.g. matrix multiplies, convolutions, normalizations). Following general software engineering best practices including support for regression testing and CI/CD flows.Collaborating with teams across NVIDIA:

• CUDA compiler team on generating optimal assembly code
• Deep learning training and inference performance teams on which layers require optimization.
• Hardware and architecture teams on the programming model for new deep learning hardware features

According to JobzMall, the average salary range for a Machine Learning Engineering Intern in NVIDIA Endeavor, 2788 San Tomas Expy, Santa Clara, CA 95051, USA is between $60,000 and $80,000 per year.

This salary range is slightly higher than the average salary range for a Machine Learning Engineering Intern position, which is typically between $45,000 and $65,000 per year. NVIDIA Endeavor is a large and highly respected technology company, so experienced and talented Machine Learning Engineering Interns may be able to negotiate higher salaries at this particular location.

NVIDIA Corp. designs and manufactures computer graphics processors, chipsets, and related multimedia software. The company operates through two segments: Graphics Processing Unit and Tegra Processor. The Graphics Processing Unit segment includes sales of the company's GeForce discrete and chipset products that supports desktop and notebook PCs plus license fees from Intel and sales of memory products. The Tegra Processors segment provides processors that deliver superior visual and multimedia experience on tablets, smart phones and gaming devices while consuming minimal power.