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Staff Machine Learning Strategic Applications Engineer

156316
San Jose, CA, United States
Dec 12, 2018

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Job Description

Description

 

Xilinx, Inc. (NASDAQ: XLNX) is the world’s leading provider of All Programmable technologies and devices, going beyond traditional programmable logic to enable both hardware and software programmability, integrate both digital and analog mixed-signal functions, and allow new levels of programmable interconnect in both monolithic and multi-die 3D ICs. The company’s products are coupled with a next-generation design environment, IP and a proven design methodology to serve a broad range of customer needs, from programmable logic to programmable systems integration.
 
This Xilinx Strategic AE will be responsible for customer Machine Learning technical engagements and to maximize Xilinx presence in North America.

Responsibilities:

  • Provide deep technical support to customers who are evaluating and designing with Xilinx machine learning solutions
  • POC design creation to demonstrate Xilinx’s values on silicon, IP in machine learning area
  • Analyze customer needs, and compare and contrast Xilinx and competitive solutions in order to maximize the customers use of Xilinx products
  • Collaborate with field and factory resources to develop and deliver technical proposals to customer project managers, engineering managers, system architects and design engineers
  • Code and implement circuits to demonstrate efficient use of Xilinx technology and competitive advantages in ML area
  • Provide all post-sales support, including lab debug,  performance analysis, software programming, and power analysis for ML workload
  • Provide regular feedback to Xilinx management and factory experts on the needs of the customer base

Qualifications: 

  • Bachelor's Degree in Electrical Engineering or Computer Science or equivalent; Master's Degree preferred
  • 5+ years of industry experience with Machine learning design flow
  • Knowledge in Deep Neural Networks, RNN/LSTM, MLP, and training and inference of a neural network
  • Experience with common machine learning framework, such as Tensorflow, MXnet, and Caffe
  • Strong programming skills, C, C++, Python
  • Strong knowledge in DSP
  • Software knowledge on Linux, Hypervisor, drivers is preferred
  • FPGA-based experience is a plus
  • Excellent written and verbal communication skills, presentations skills, and the ability to work with multiple groups

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