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!
You will be part of an R&D team that develops runtime for high-performance AI inference accelerators on Xilinx's FPGA. Xilinx unique reconfigurable platform enables the design of optimized domain-specific architecture for a variety of Deep Learning Algorithms. In this position, you will work on developing high-performance and low latency runtime execution frameworks to support AI accelerators for Deep Learning.
You will work on projects critical to Xilinx's growth, with opportunities to move among various teams and projects. You are versatile, display leadership qualities and are enthusiastic about tackling new problems across the full stack as we continue to push technology forward. Most of all, you are driven to find creative solutions where solutions may not exist yet.
• Develop runtime execution frameworks to support AI accelerators for Deep Learning with well-defined C++ and Python API.
• Develop support for executing generic dataflow graphs in a heterogeneous computing environment with a mix of FPGAs and CPUs.
• Collaborate with members of the hardware architecture teams to accelerate the next generation of Deep Learning software.
• MS/Ph.D. degree in Computer Science with 2+ years of industry experience or BA/BS degree in Computer Science with 5+ years of industry experience
• Passion for developing high-performance runtime code for SOC, GPU, and CPU
• Expertise in C++11/14
• A solid foundation in data structures, computer arithmetic, algorithms and software design with strong analytical and debugging skills
• Excellent communication and collaboration skills
• Experience with the internals of one or more frameworks: Caffe2, Pytroch, MxNet or Tensorflow
• Experience with AVX accelerated libraries like MKL