Responsibilities:
●Training/inference performance requirement analysis
●Training/inference performance modelling and mini-benchmark design
●Benchmark application performance profiling and optimization
●Support hardware designers for hardware performance goal
 
Minimum Qualifications:
●CS/EE MS 3yrs+ relate work experience.
●Familiar with popular framework like Tensorflow, Caffe, Mxnet.
●Familiar with popular CNN, RNN models like Resnet50, Googlenet, VGG16.
●Experienced in NPU/GPGPU/HPC performance profiling and tuning experience.
●Strong coding skills in C/C++ and Python.
●Familiar with dev/build utility (like git, CMake, Bazel etc.) and shell script(like bash).
●Good communication skill and technical leadership
 
Preferred Qualifications:
●Experience in using HW emulation platform, including Palladium, Zebu, or FPGA.
●Experience with Resnet50 training performance tuning.
●Experience in NPU training performance profiling and optimization
●Experience in CUDA/cuDNN development and performance tuning.
●Experience in GPU driver performance tuning.