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Deep Learning Software Engineer(Contractor)

Beijing Shi, China, China
Mar 17, 2021


Job Description


At Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. ARE YOU bold, collaborative, and creative? At Xilinx, we hire and develop leaders and innovators who want to revolutionize the world of technology. We believe that by embracing diverse ideas, pushing boundaries, and working together as ONEXILINX, anything is possible.

Our culture of innovation began with the invention of the Field Programmable Gate Array (FPGA), and with the 2018 introduction of our Adaptive Compute Acceleration Platform (ACAP), has made a quantum leap in capability, solidifying our role as the adaptable platform supplier of choice. From the start, we have always believed in providing inventors with products and platforms that are infinitely adaptable. From self-driving cars, to world-record genome processing, to AI and big data, to the world's first 5G networks, we empower the world's builders and visionaries whose ideas solve every day problems and enhance people's lives.

If you are PASSIONATE, ADAPTABLE, and INNOVATIVE, Xilinx is the right place for you! At Xilinx we care deeply about creating meaningful development experiences while building a strong sense of belonging and connection. We foster an environment of empowered learning, wellness, community engagement, and recognition, so you can focus on work that matters - world class technology that improves the way we live and work. We are ONEXILINX.

Title: Deep learning software engineer

 Job description

1. Develop Neural network accelerator software toolchain

2. Analyse and test software implementations to make sure consistency between software and hardware

3. Modelzoo benchmarking, testing

4. Write design and development documents

Education Requirements
Bachelor or above in CS/EE or related

Years of Experience

1. Above 3 years of C++/Python coding

2. Skilled in Linux programing and developing tools, such as Git, Cmake.

Refer to the Talent Network

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