Xiaoquan Kong
Software Engineer, Machine Learning at Google
Greater Seattle Area United States
Summary
🤩
Rockstar🎓
Top SchoolXiaoquan Kong is a software engineer specializing in applied machine learning with 14 years of experience and 9+ years building production ML systems at Baidu, Alibaba, Geely and now Meta. A Google Developer Expert in Machine Learning & Cloud since 2018, he blends hands-on engineering—shipping RAG, LLM fine-tuning and agentic systems—with developer advocacy and mentoring roles in TensorFlow and Google Summer of Code. He’s an active open-source contributor (notably to Rasa and TensorFlow Addons) and author of multiple books on conversational AI and spaCy, bringing both practitioner depth and clear technical communication. At Duke he developed a graduate Reinforcement Learning course and built Qubit, an agentic coding assistant, reflecting a rare mix of production delivery, research-driven teaching, and tooling for developer productivity.
14 years of coding experience
8 years of employment as a software developer
Master of Engineering - MEng, Artificial Intelligence for Product Innovation, Master of Engineering - MEng, Artificial Intelligence for Product Innovation at Duke UniversityBachelor's degree, Life Sciences, Bachelor's degree, Life Sciences at Anqing Normal University
English, Chinese
Github Skills (19)
python10
machine-learning10
tensorflow10
rasa10
natural-language-processing10
neural-network10
transformer10
nlp10
documentation10
testing9
deeplearning-ai9
deep-learning9
struct8
data-structures8
data-structure8
Programming languages (10)
Github contributions (5)
tensorflow/addons
Apr 2019 - Nov 2021
Role in this project:
ML Engineer
ML EngineerContributions:13 reviews, 8 commits, 10 PRs in 2 years 7 months
Contributions summary:Xiaoquan primarily contributed to the TensorFlow Addons library by extending and improving the functionality of the CRF (Conditional Random Field) model, a crucial component for sequence labeling tasks in machine learning. Their work included adding support for tf.Variable and tf.SparseTensor types within the TensorLike type, fixing a CRF-related bug, and developing a CRF model wrapper to streamline its usage within the library. Furthermore, they were responsible for moving the CRF wrapper module to tfa.text.
python2-xdeep-learningaddonssig
RasaHQ/rasa
Nov 2017 - Jan 2021
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:21 reviews, 130 commits, 23 PRs in 3 years 2 months
Contributions summary:Xiaoquan's contributions focused on enhancing the Rasa NLU framework. They implemented a dynamic project loading feature and improved the existing cloud storage integration. They also addressed bugs related to project loading and ensured no-duplicate lists in projects, which improved the framework's reliability. Additionally, the user worked on improvements in the count vector featurizer to utilize tokens.
nlupythonbotspeech-recognitionbotkit
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.