Jingning Tang
Software Engineer at Google
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolJingning Tang is a software engineer with nine years of experience specializing in deep learning inference, GPU algorithms, and mmWave radar signal processing. Currently at Google working on GPU performance, he previously developed AI framework and compiler-level kernels at AMD, including work on Triton, FlashAttention, GEMM and MoE. His background blends radar DSP and system engineering—building beamforming super-resolution and occupancy-grid mapping pipelines using CUDA, C++, Python and MATLAB—grounded in an MS in ECE from UIUC. Comfortable moving between low-level GPU/kernel optimization and high-level algorithm design, he brings a practical track record of turning signal-processing research into production-ready inference and compute primitives. An often-overlooked strength is his cross-domain fluency in RF hardware constraints and compiler-level software, enabling optimizations that span silicon to system.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS ECE, Master of Science - MS ECE at University of Illinois Urbana-Champaign
Github Skills (41)
python10
data-science10
machine-learning10
ml10
triton10
code-generation10
deep-learning10
tensorflow10
deep-neural-networks10
neural-network10
programming-language9
tensorboard9
compiler9
memory-efficient8
chainer7
Programming languages (5)
Github contributions (5)
jtang10/ss_pred_tf
Sep 2017 - Oct 2017
Contributions:18 commits, 16 pushes, 1 branch in 19 days
jtang10/go-tensorrt
May 2020 - May 2020
Go binding to TensorRT C API to do inference with pre-trained model in Go
Contributions:11 pushes, 2 branches in 27 days
golangapipre-trained-modelgo-bindingto-do
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.