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AI Compiler Engineer

156774
San Jose, CA, United States
Jun 25, 2019

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Job Description

Description

At Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. ARE YOU bold, collaborative, and creative? At Xilinx, we hire and develop leaders and innovators who want to revolutionize the world of technology.  We believe that by embracing diverse ideas, pushing boundaries, and working together as ONEXILINX, anything is possible. 

Our culture of innovation began with the invention of the Field Programmable Gate Array (FPGA), and with the 2018 introduction of our Adaptive Compute Acceleration Platform (ACAP), has made a quantum leap in capability, solidifying our role as the adaptable platform supplier of choice.  From the start, we have always believed in providing inventors with products and platforms that are infinitely adaptable. From self-driving cars, to world-record genome processing, to AI and big data, to the world’s first 5G networks, we empower the world’s builders and visionaries whose ideas solve every day problems and enhance people’s lives.

With the exponential growth in AI inference deployment, the state of the art in AI models are rapidly evolving and will continue for the foreseeable future. Domain-Specific Architectures are required for efficient AI inference. Only adaptable hardware platforms can provide efficient DSAs for the latest AI models. The Xilinx AI software platform makes Xilinx’s adaptable hardware accessible to all software and AI developers by providing a familiar programming interface and comprehensive libraries. The result is Real Time AI Inference up to 4X faster than GPUs and 10X less power than CPUs. 

If you are PASSIONATE, ADAPTABLE, and INNOVATIVE, Xilinx is the right place for you!  At Xilinx we care deeply about creating meaningful development experiences while building a strong sense of belonging and connection. We foster an environment of empowered learning, wellness, community engagement, and recognition, so you can focus on work that matters – world class technology that improves the way we live and work.  We are ONEXILINX.

You will be part of an R&D team that develops high-performance AI inference accelerators. Xilinx’s unique reconfigurable platform enables the design of optimized domain specific architecture for a variety of Deep Learning Algorithms. The ideal candidate will have worked on new instruction set architectures which may include CPU, NPU, GPU, Domain Specific Architectures and other forms of compute.
 
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.
 
Responsibilities:
  • Develop optimizing compilers, code generators and runtime execution frameworks for AI accelerators for Deep Learning.
  • Work on compiling an intermediate graph representation (IR) to target specific code and define the interfaces to runtime systems and libraries. 
  • Collaborate with members of the software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. 
  • You will work on integrating the backend in a variety of deep learning frameworks - Caffe2, PyTorch, MxNet/TVM, Tensorflow

Minimum Qualifications
  • 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 and optimizing compilers for modern architectures
  • Working knowledge of compiler architecture, front-end and middle-end optimizations, scheduling, register allocation, back-end code generation
  • High-level C++ programming expertise
  • A solid foundation in data structures, computer arithmetic, algorithms and software design with strong analytical and debugging skills
  • Excellent communication and collaboration skills
Preferred Qualifications
  • Experience with the internals of one or more frameworks: Caffe2, PyTorch, MxNet or Tensorflow
  • Experience with neural networks inference on dedicated SOC
  • Research experience in developing compiler flow for custom processor architectures
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