# Zeqi Qiu > Senior Software Engineer at Bytedance Location: Mountain View, California, United States Profile: https://flows.cv/zeqi ## Work Experience ### Senior Software Engineer Technical Lead @ ByteDance Jan 2022 – Present | San Jose, California, United States Worked on large-scale infrastructure platforms across Edge, Network, Finance, and AI, building multiple 0→1 and evolution-stage systems used by global teams. Focused on platform architecture, automation, and AI-driven efficiency for overseas infrastructure operations. ### Full Stack Engineer @ Landing AI Jan 2019 – Jan 2022 | 帕洛阿尔托， CA， 美国 Build Landing Lens AI Platform supporting data ingestion, labeling, exporting, training and model inference; Build Onprem solution for Landing Lens AI Platform, supports onprem deployment; ### Graduate Student @ Carnegie Mellon University Jan 2018 – Jan 2018 | Pittsburgh, Pennsylvania 10703 Deep Reinforcement Learning and Control (grade: A) 10701 Introduction to Machine Learning(PhD) (grade: A) 15688 Practical Data Science (grade: A) 18797 Machine Learning and Signal Processing (grade: A) Present course: 15688 Distributed System 11785 Deep Learning 16720 Computer Vision ### Software Development Engineer Intern @ Tencent Jan 2018 – Jan 2018 | Shenzhen, Guangdong, China Keyword: Spark, Scala, C++, Machine Learning, Recommendation System Used Spark to deal with and manage huge data in SQL and build a Xgboost model for Click Through Rate Prediction model Built a Coarse Ranked Recall Model to ranked the articles and recall the top thousands articles to Fine Ranked Recall Model Released the recommendation system online and serve for the recommendation of the pictures and articles in QQ ### Graduate Student @ Carnegie Mellon University Silicon Valley Jan 2017 – Jan 2017 15619 Cloud Computing 18600 Introduction to Computer System ### Undergraduate Research Assistant @ Sun Yat-Sen University Jan 2016 – Jan 2017 | Guangzhou, Guangdong, China Researched on Reinforcement Learning with Professor Paul Weng. Solved the problem of controlling data centers considering the balance of power consuming and Quality of Service Modeled the problem as a Markov Decision Process and used projected gradient descent to solve the problem Used Model-Based Reinforcement Learning to approximate result of the Model-Free Problem Got a 15% normalized cumulated cost decreased compared to baseline (MPC) ### Undergraduate Research Assistant @ South China University of Technology Jan 2015 – Jan 2017 | Guangzhou, Guangdong, China Researched on Interference of Wireless Body Area Network with Professor Quansheng Guan. Researched on reducing the interference among several Wireless Body Area Networks. Modeled problem as a Multi-Armed Bandit problem with UCB and ε-Greedy solution for channel sensing Implemented the algorithm with nesC language with TinyOS system on TI CC2530 SoC Solved co-channel interference problem among several Body Area Network in a crowded circumstance Obtained a patent for this method ### Undergraduate Research Assistant @ Tsinghua University Jan 2016 – Jan 2017 Helped finish the experiments for the algorithms and optimized the code and V-Tree data structure Solved the problem of indexing the moving objects on road networks and finding the k nearest moving objects Designed a data structure V-Tree which support efficient kNN search and dynamical updates of moving objects Designed a kNN search algorithm using V-Tree by pruning large numbers of irrelevant vertices in the road network Implemented algorithm and all experiments with C++ and optimized the code to reduce the average query time ## Education ### Master of Science - MS in Electrical and Computer Engineering Carnegie Mellon University ### Master's degree in Electrical and Electronics Engineering Carnegie Mellon University Silicon Valley ### Bachelor's degree in Information Engineering South China University of Technology ## Contact & Social - LinkedIn: https://linkedin.com/in/zeqiqiu0816 --- Source: https://flows.cv/zeqi JSON Resume: https://flows.cv/zeqi/resume.json Last updated: 2026-04-01