DescriptionXilinx 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).
Product Planning and Competitive Analytics Engineer
You will be part Product Planning and Competitive Analytics Team that helps define next generation silicon technology. 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 to help push technology forward.
• Characterize, analyze and evaluate Data Center workloads (such as Image Classification, Speech Recognition, and Natural Language processing) on the basis of performance, cost, model accuracy, latency and power.
• Work closely with team members to assist in defining next generation silicon technology.
• Create presentations, white papers, for both internal and external publications.
• BS/MS degree in Electrical Engineering or Computer Science or BA/BS degree in Electrical Engineering or Computer Science with industry experience.
• Solid engineering and coding skills. Ability to write production quality code. Experience in C++, Python, and other equivalent languages is a plus.
• Familiarity with concepts of Machine Learning models and Machine Learning frameworks.
• Experience with implementing machine learning computation framework on GPU, CPU or FPGA/ACAP device.
• Experience with developing acceleration application using OpenCL or CUDA.
• Experience with Machine Learning frameworks like Caffe, MxNet or Tensorflow.
• Solid engineering and coding skills. Ability to write high-performance production quality code. Experience in C++, Python, and other equivalent languages is a plus.