Yao Wang
Principle Machine Learning Engineer at The Apache Software Foundation
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolYao Wang is a principal machine learning engineer with a decade of experience building ML infrastructure, compilers, and production inference platforms across startups and hyperscalers. Based in the San Francisco Bay Area, he led AI infrastructure at an AI unicorn and was a core designer and tech lead for AWS SageMaker Neo, helping make model compilation and deployment widely adopted. He is an active Apache TVM contributor and PPMC member, with hands-on work implementing and optimizing operators, schedulers, and graph-level transforms in TVM/NNVM that power efficient CPU/GPU inference. At Unity he continues to bridge research-grade compiler techniques with production systems, and his background spans both backend/server work and front-end documentation improvements (e.g., MXNet) that improve developer UX. Trained in CS and mechanical engineering, Yao combines low-level performance tuning with system architecture and a pragmatic focus on observability and production reliability.
10 years of coding experience
6 years of employment as a software developer
Master's Degree Computer Science, Master's Degree Computer Science at University of Southern CaliforniaBachelor of Engineering Mechantronic Engineering, Bachelor of Engineering Mechantronic Engineering at Beijing Institute of TechnologyBachelors Mechanical Engineering, Bachelors Mechanical Engineering at Purdue University Northwest
English, Chinese
Github Skills (34)
tvm10
c-language10
python10
css10
mxnet10
machine-learning10
data-export10
inference10
exporter10
deeplearning-ai10
deep-learning10
ai10
compiler-optimization10
object-detection10
exports10
Programming languages (6)
Github contributions (5)
apache/mxnet
Oct 2016 - Dec 2017
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
Front-end Developer
Front-end DeveloperContributions:105 commits, 154 PRs, 166 comments in 1 year 1 month
Contributions summary:Yao primarily focused on improving the user interface and documentation for the MXNet project. Their commits centered around fixing CSS issues, modifying navigation bars, and adjusting the layout for different screen sizes. They also addressed broken links, improved the model zoo page style, and added a search function, indicating a focus on enhancing the user experience and making the documentation more accessible.
pythonschedulerdataflowmutationdata-science
apache/tvm
Dec 2017 - Feb 2021
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:74 reviews, 68 commits, 181 PRs in 3 years 2 months
Contributions summary:Yao's commits primarily focus on implementing and optimizing operators for the Apache TVM deep learning compiler stack. They added a base scheduler for dense operators, and introduced new operators like those for SSD (Single Shot MultiBox Detector) object detection, which included implementing an IR builder. Additional contributions include the integration of optimization techniques such as weight transforms within the dense layer and various improvements to existing operators to enhance performance, as well as the addition of a "where" operator.
metalvulkancompilertensoropencl
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