Xuechen Li
Member Of Technical Staff at xAI
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXuechen Li is a Machine Learning engineer and researcher with 11 years of experience, currently a Member of Technical Staff at xAI working on post-training, large-scale RL and product-driven research. He holds a PhD in Computer Science from Stanford and has a track record at top research labs including Google (AI Resident, student researcher) and Microsoft (research intern deploying differentially private ML into Outlook). His open-source contributions span influential projects—helping train Stanford’s Alpaca models and improving core functionality in google-research/torchsde and the HELM evaluation framework—demonstrating strengths in training pipelines, weight management, numerical SDE tooling, and copyright-related evaluation metrics. Xuechen’s work bridges deep research and production: he has shipped privacy-preserving ML into product and contributed utility fixes and metrics that enable safer, more transparent model evaluation. Based in Palo Alto, he combines academic rigor with practical engineering, often focusing on under-the-hood reliability like dependency fixes, import robustness, and model weight recovery. Colleagues would note his penchant for translating complex theory into reproducible code and measurable product impact.
10 years of coding experience
2 years of employment as a software developer
Beijing No.4 High SchoolBachelor of Science - BS (Hons), Bachelor of Science - BS (Hons) at University of TorontoDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Stanford University
Chinese, English, French
Github Skills (17)
transformers10
pytorch10
python10
nltk10
machine-learning10
differential-equations10
deep-learning10
trainings10
modeling10
data-science9
language-model9
deep-neural-networks9
neural-network9
nlp8
data-analysis8
Programming languages (8)
Github contributions (5)
google-research/torchsde
Jul 2020 - May 2021
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:4 releases, 93 reviews, 101 commits in 10 months
Contributions summary:Xuechen replaced placeholder packages and fixed import issues, indicating involvement in project setup and dependency management. They also addressed brownian import issues by changing relevant code, indicating a focus on core libraries. Further, they added functionality to handle "alternative color" and "to device" calls for a brownian tree, showing engagement with internal structures and potential refactoring efforts.
cudastochastic-differential-equationsdifferentiablesensitivity-analysisgpu
tatsu-lab/stanford_alpaca
Mar 2023 - Jun 2023
Code and documentation to train Stanford's Alpaca models, and generate the data.
Role in this project:ML Engineer
ML EngineerContributions:13 PRs, 10 pushes, 10 branches in 3 months
Contributions summary:Xuechen primarily contributed to the training and weight management aspects of the Alpaca model. Their commits involved modifying the `train.py` script, indicating work on training code and related configurations. Furthermore, the user introduced and refined the `weight_diff.py` script, demonstrating an understanding of weight difference calculations and model recovery. This suggests the user focused on model training, optimization, and the handling of model weights.
deep-learninginstruction-followinglanguage-model
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