Description
At Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. ARE YOU bold, collaborative, and creative? We 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 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 improve people's lives.
Xilinx is looking for a deep learning compiler engineer to build the compiler and software tool chain for deploying custom ML networks optimized for latency and power to ACAP. In this position, you will contribute, develop and enhance Xilinx ML compiler by building custom optimizations and transformations (operator fusion, tiling, memory layout across various cache hierarchy) targeted to ACAP on top of open-source technoogy like LLVM, TVM, MLIR. You will also work on performance modeling tools that predict the performance with various level of accuracy and abstraction to be used as part of the compiler optimizations/explorations.
ACAP is unique platform in the industry where one can create a custom hardware architecture target to any custom ML network, thereby providing best power-performance at the fastest time to market. Your work in the compiler team will enable that!!
Years of Experience