Xilinx develops highly flexible and adaptive processing platforms that enable rapid innovation across a variety of technologies - from the endpoint to the edge to the cloud. Xilinx is the inventor of the FPGA, hardware programmable SoCs and the ACAP (Adaptive Compute Acceleration Platform), designed to deliver the most dynamic processor technology in the industry and enable the adaptable, intelligent and connected world of the future in a multitude of markets including Data Center (Compute, Storage and Networking); Wireless/5G and Wired Communications; Automotive/ADAS; Emulation & Prototyping; Aerospace & Defense; Industrial Scientific & Medical, and others. Xilinx's core strengths simultaneously address major industry trends including the explosion of data, heterogeneous computing after Moore's Law, and the dawn of artificial intelligence (AI).
Our global team is growing and we are looking for bold, collaborative and creative people to help us lead the industry transformation to build an adaptable intelligent world. We believe that by embracing diverse ideas, striving for excellence in all that we do, and working together as a unified team, we can accomplish anything. Come do your best work and live your best life as part of the ONEXILINX team!
We are looking for a Software Engineering Intern with an interest in AL and ML to help our team with the following:
• Developing Bare Metal and/or Linux drivers for AI acceleration engines using Xilinx SOCs
• Prototype and develop solutions for AI/ML frameworks.
• Evaluate AI/ML prototypes on Xilinx Solutions.
• Evaluating AI solutions developed by Xilinx and performing comparative analysis against other industry solutions.
• Work with different teams to identify problems and create solutions
• Delivering software solutions in line with product roadmap on time with high quality.
• Willingness to learn skills, tools and methods to advance the quality, consistency, and timeliness of Xilinx software products
Currently, pursuing a Undergraduate or Masters Degree in Electrical Engineering or Computer Science
Preferred start date: January 2022
Duration: 3-6 months
Hours: part-time, 20 hours per week