Zhengqi Liu
Frontend Engineer at Baidu, Inc.
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top School
Top expert inAdvanced Chinese Natural Language Processing and Machine Learning Technologies
Zhengqi Liu is a Frontend Engineer based in the San Francisco Bay Area with seven years of software engineering experience and an MEng in Electronic and Computer Engineering from UC Santa Cruz. Currently at Baidu, he blends frontend expertise with deep backend and MLOps knowledge demonstrated by substantial contributions to the PaddlePaddle ecosystem—implementing core operators, improving inference APIs, and enhancing PaddleNLP generation and FasterTransformer support. He has a track record of shipping reliable tests and documentation across major open-source ML projects, showing attention to both code correctness and developer experience. Prior roles include AWS IoT prototyping and hands-on model and inference work, giving him a practical bridge between edge deployment and large-scale ML systems. Colleagues can expect a pragmatic engineer who moves fluidly between front-end product work and low-level ML infrastructure, often improving performance and testability in the process.
7 years of coding experience
High School Affiliated to Shanghai Jiao Tong UniversityBachelor of Engineering - BE, Electronic Information Science and Technology, Bachelor of Engineering - BE, Electronic Information Science and Technology at Beijing University of Posts and TelecommunicationsUniversity of California Santa Cruz
Stackoverflow
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Github Skills (27)
transformers10
unit-testing10
c-language10
python10
machine-learning10
api-documentation10
deep-learning10
neural-network10
paddlepaddle10
nlp10
cprogramming-language10
modeling10
documentation10
develop9
text-generation9
Programming languages (4)
Github contributions (5)
PaddlePaddle/PaddleNLP
Feb 2021 - Jan 2023
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Role in this project:
Back-end & MLOps Engineer
Back-end & MLOps EngineerContributions:454 reviews, 171 commits, 337 PRs in 1 year 11 months
Contributions summary:Zhengqi made significant contributions to the paddlenlp/paddlenlp repository, primarily focusing on enhancing the FasterTransformer and supporting Text-To-Text Transfer Transformer (T5) with unit tests and generation improvements. Their work involved integrating custom operators, supporting multi-lingual models, and optimizing the existing generation process through dynamic code generation. The contributions include bug fixes, performance improvements, and ensuring the stability of various generation workflows, indicating a focus on MLOps practices.
extractionsemantic-similaritybertnlp-tasksfinetuning
PaddlePaddle/models
Feb 2020 - Feb 2021
Officially maintained, supported by PaddlePaddle, including CV, NLP, Speech, Rec, TS, big models and so on.
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:35 reviews, 35 commits, 73 PRs in 11 months
Contributions summary:Zhengqi primarily contributed to the PaddlePaddle models repository by updating APIs and documentation related to machine learning models, specifically focusing on the similarity_net and transformer models. Their work involved code modifications in Python files, including adjustments to training and evaluation processes, indicating a focus on model functionality and performance. They also fixed predict methods and simplified transformer reader which suggests a hands-on role in model development and deployment.
nlpdeep-learningpaddlepaddlerecommendationcomputer-vision
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