Xinyue Ruan
Software Engineer at Databricks
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolXinyue Ruan is a software engineer with five years' experience building scalable ML infrastructure and observability features, currently at Databricks after roles at Microsoft and Google. She contributes to high-profile open-source projects like MLflow and SynapseML, focusing on Spark/PySpark model tracking, autologging, and improving prediction and logging pipelines. Her background blends quantitative finance internships and a Columbia MS with hands-on engineering, giving her a strong foundation in model validation and production tooling. Known for pragmatic problem-solving, she has a track record of fixing tricky Spark prediction issues and expanding transformer tracking support in widely used ML platforms.
5 years of coding experience
3 years of employment as a software developer
Bachelor of Economics Financial Engineering, Bachelor of Economics Financial Engineering at Central University of Finance and EconomicsMaster of Science - MS Operations Research, Master of Science - MS Operations Research at Columbia UniversityUniversity of California, Los Angeles
English, Chinese
Github Skills (9)
apache-spark10
machine-learning10
pyspark10
mlflow10
modeling9
scala9
feature-engineering9
trainings9
logging8
Programming languages (9)
Github contributions (5)
microsoft/SynapseML
May 2021 - Jan 2023
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Role in this project:
Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:131 reviews, 375 commits, 151 PRs in 1 year 9 months
Contributions summary:Xinyue contributed to the development of the MMLSpark logging infrastructure, indicating a focus on improving the system's observability. The code changes involve modifications to the `TrainClassifier` class and the `Featurize` class, suggesting involvement in machine learning model training and feature engineering within the SynapseML framework. The user also added logging capabilities for better debugging and monitoring of the model training process.
machine-learningportingpythonsparkpyspark
mlflow/mlflow
Mar 2022 - Nov 2022
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Role in this project:ML Engineer
ML EngineerContributions:10 releases, 3370 reviews, 10 commits in 8 months
Contributions summary:Xinyue's commits primarily focus on integrating and enhancing Spark transformers tracking with MLflow, including support for transformer model tracking and the implementation of predict functionality. They addressed comments, made improvements to code, and corrected spark prediction issues. The user also worked on expanding autologging capabilities for PySpark ML models, showcasing expertise in model tracking and machine learning engineering.
aimlflowmlmodelmachine-learningml
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