Yuyang Xie
Member Of Technical Staff at xAI
Los Gatos, California, United States
Summary
👤
Senior🎓
Top SchoolYuyang Xie is an AI infrastructure engineer and researcher with 11 years of experience building production-grade ML systems and leading LLM efforts across startups and cloud giants. He helped launch Higgs-Llama-3-70B-v2 at Boson AI and led audio-language research and productization there, while earlier founding the Vertex AI Feature Store at Google Cloud and spearheading Robinhood’s third-generation feature store and generative AI infrastructure. Equally comfortable in code and strategy, he has owned end-to-end LLM pipelines from data curation to GPU cluster ops and monetized fintech LLM solutions in regulated environments. A competitive data scientist and open-source contributor (Kaggle Competition Master, contributions to the xlearn scikit-learn interface), he reads and implements research daily and keeps a hands-on habit of shipping tools that bridge research and production. Based in Los Gatos, he combines deep systems expertise with product instincts to move high-impact AI projects from prototype to scale.
11 years of coding experience
11 years of employment as a software developer
Master of Science (MSc) Mechanical Engineering, Master of Science (MSc) Mechanical Engineering at The University of Texas at AustinHong Kong University of Science and Technology (HKUST)
Chinese, Chinese, English
Github Skills (11)
scikit-learn10
factoring10
machine-learning10
factors10
2factor10
python10
factorization10
scikit10
data-analysis8
numpy8
data-science8
Programming languages (10)
Github contributions (5)
aksnzhy/xlearn
Feb 2018 - Apr 2018
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 4 PRs, 17 comments in 1 month
Contributions summary:Yuyang contributed to the scikit-learn interface for the xlearn library, adding and improving the existing machine learning models, including the LR, FM and FFM models. They implemented a new FMModel example and updated parameter descriptions. Moreover, the user updated the fit method to support the legacy Python 2, and added the check_X_y function to the evaluation set. The user added the functionality of extracting weights from the txt file, updated documentation, and added the n_jobs parameter.
pythonffmclistatisticsdata-science
randxie/alpha-pilot-team-deadlock
Dec 2018 - Feb 2020
Alpha Pilot Team Deadlock
Contributions:196 commits, 6 PRs, 8 pushes in 1 year 1 month
pilotdeadlock
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