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Product Marketing Engineer - Software Products

157142
San Jose, CA, United States
May 8, 2019

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Job Description

Description

Xilinx is the leading provider of All Programmable FPGAs, SoCs, MPSoCs and 3D ICs. Xilinx's all-programmable devices are designed into tens of thousands of products that improve the quality of the everyday lives of billions of people worldwide. For over 30 years, Xilinx has been behind some of the greatest advancements in technology and science - from the industry's first fabless semiconductor model to the NASA Curiosity Mars Rover, to today's autonomous vehicles and hyperscale data centers. Xilinx uniquely enables applications that are both software-defined, yet hardware optimized - enabling smart, connected and differentiated applications across technology's biggest megatrends, including Machine Learning, 5G Wireless, Embedded Vision, Industrial IoT, Cloud Computing, Prototyping/Emulation, and more.

 

The Product Marketing Engineer position is in the Software and AI marketing group, located in San Jose (California) or Longmont (Colorado), for an expert marketing engineer to focus on scaling technical expertise and driving product requirements. The successful candidate will work closely with customers, the Xilinx field, market segment architects and R&D to enable the next generation of designs.

 

 

Responsibilities:

  • Drive definition of Xilinx software-defined algorithm acceleration tool flows and hardware-accelerated libraries
  • Define integration of machine learning / AI into hardware/software acceleration systems for both data center and edge / IoT applications
  • Create marketing requirements documents, including proof-of-concept designs, illustrating design flows, methodologies, and competitive differentiation for algorithm acceleration on Xilinx FPGAs and ACAPs
  • Drive the evolution of tools and features related to Xilinx software acceleration by collaborating with engineering and helping drive tool features.
  • Drive best-in-class development flows and methodologies for software acceleration
  • Represent the needs of end-users, evaluate market trends and competition, and use this information to determine what features to build for software acceleration tools

 

Job Requirements:

 

  • 10+ years of industry experience with GPU programming, OpenCL or CUDA optimization, and debug techniques.
  • Strong CUDA, OpenCL, C/C++ programming and Python scripting skills.
  • Solid understanding of machine architectures and micro-architectural performance considerations.
  • Experience with parallel programming and data flow graphs.
  • Experience with VLIW compilers and architectures is a plus.
  • Experience with explaining and evangelizing advanced technical systems is a plus.
  • Experience with FPGA design is a plus.
  • Experience with machine learning inference is a plus.
  • Experience with Jupyter Notebooks is a plus.
  • Excellent written and verbal communication skills, presentations skills, and the ability to work with multiple groups.

 

Education/Experience:

 

• BS/MS (Master's Degree preferred) in CS/EE with a minimum of 10+ years’ experience with GPU programming using OpenCL or CUDA, optimization and debug techniques

Job Requirements:

 

  • 10+ years of industry experience with GPU programming, OpenCL or CUDA optimization, and debug techniques.
  • Strong CUDA, OpenCL, C/C++ programming and Python scripting skills.
  • Solid understanding of machine architectures and micro-architectural performance considerations.
  • Experience with parallel programming and data flow graphs.
  • Experience with VLIW compilers and architectures is a plus.
  • Experience with explaining and evangelizing advanced technical systems is a plus.
  • Experience with FPGA design is a plus.
  • Experience with machine learning inference is a plus.
  • Experience with Jupyter Notebooks is a plus.
  • Excellent written and verbal communication skills, presentations skills, and the ability to work with multiple groups.

 

Education/Experience:

 

• BS/MS (Master's Degree preferred) in CS/EE with a minimum of 10+ years’ experience with GPU programming using OpenCL or CUDA, optimization and debug techniques

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