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Staff Design Engineer (Machine Learning)

156419
San Jose, CA, United States
Jan 4, 2019

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Job Description

Description

Xilinx is the world's leading provider of All Programmable FPGAs, SoCs and 3D ICs. These industry-leading devices are coupled with a next-generation design environment and IP to serve a broad range of customer needs, from programmable logic to programmable systems integration. Our All Programmable devices underpin today's most advanced electronics. Among the broad range of end markets we serve are:

  • Aerospace/Defense
  • Automotive
  • Broadcast
  • Consumer
  • High Performance Computing
  • Industrial / Scientific / Medical (ISM)
  • Wired
  • Wireless

 

Design, develop and test future generation technologies for machine learning and artificial intelligence. Specifically, develop new hardware and software solutions including electronic equipment and systems, for accelerating data center workloads such as machine learning. Architect future silicon and software for solving web-scale class machine learning technology through power-efficient embedded machine learning solutions. Develop machine learning networks together with the associated tasks of training, inference and optimizations to manage compute workload and memory IO. Design machine learning algorithms, deep convolutional networks (DCNN), recurrent and other networks. Utilize network training algorithms and state-of-the-art techniques for CNN weight compression, quantization and pruning strategies. Parallelize and partition algorithms across highly parallel computing platforms, then analyze and benchmark performance of the resulting implementation.


#LI-DNI

Implementation of complex signal processing on at least one of the following platforms: FPGAs, ASIC, ASSP, GPP, GPU or DSP;Techniques for optimizing CNNs to minimize off-chip memory bandwidth requirements, storage requirements and to minimize compute requirements;Programming language such as C/C++, Python, or related; and,Machine learning frameworks such as TensorFlow, PyTorch, Caffe, or related.

Education Requirement:
  • Master’s degree or foreign equivalent in Electrical Engineering, Computer Science, or related field.
Experience Requirement:
  • 3 years of experience as Design Engineer, Hardware/Software Engineer, or related occupation.
Alternate Requirements:             
  • Will also accept a Ph.D. or foreign equivalent in Electrical Engineering, Computer Science, or related field and 1 year of experience as Design Engineer, Hardware/Software Engineer, or related occupation.

Special Requirements: 

  • Must have at least 1 year of prior work experience in each of the following: 
    1. Implementation of complex signal processing on at least one of the following platforms: FPGAs, ASIC, ASSP, GPP, GPU or DSP;
    2. Techniques for optimizing CNNs to minimize off-chip memory bandwidth requirements, storage requirements and to minimize compute requirements;
    3. Programming language such as C/C++, Python, or related; and,
    4. Machine learning frameworks such as TensorFlow, PyTorch, Caffe, or related.
#LI-DNI
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