Matthew Roeschke
Senior Software Engineer at NVIDIA
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMatthew Roeschke is a Senior Software Engineer in San Francisco with 11 years of experience building data infrastructure, ETL pipelines, and production tooling that bridge data science and engineering. A core pandas contributor and active maintainer across high-profile open-source projects like cuDF, cuML, and CuPy, he brings deep expertise in dataframe semantics, GPU-accelerated data processing, and performance-focused backend work. At NVIDIA and prior roles he’s improved library APIs, fixed tricky reindexing and aggregation bugs, and implemented streaming/windowed analytics features for time-series workloads. He pairs hands-on coding—optimizing algorithms, refactoring for modern APIs, and improving CI/CD—with practical cloud and DevOps experience, having reduced GCP costs by 35% at Genentech. His background in environmental engineering and applied data science informs a pragmatic approach to real-world data quality, monitoring, and scalable transformation problems.
11 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.), Environmental Engineering Science, Bachelor of Science (B.S.), Environmental Engineering Science at University of California, Berkeley
German, English
Github Skills (33)
algorithm10
realtime10
pytest10
python10
testing10
pandas10
cudf10
machine-learning-algorithms10
indexing10
cicd10
numpy10
gpu10
cupy10
cuda10
cuml10
Programming languages (10)
Github contributions (5)
pandas-dev/pandas
Nov 2016 - Jan 2023
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:1 release, 10111 reviews, 892 commits in 6 years 3 months
Contributions summary:Matthew contributed to bug fixes, implemented enhancements, and managed the infrastructure for the pandas project. They addressed issues related to data type conversions within the library, including issues with extension types. The user also worked on the project's tooling, including improvements to the CI/CD pipeline and build processes. Their contributions impacted the stability and maintainability of the pandas library.
data-analysisdata-structuredata-structurespythonpandas
NVIDIA/cudf
Jun 2022 - Jul 2026
cuDF - GPU DataFrame Library
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:1714 reviews, 1054 PRs, 7 pushes in 4 years 1 month
Contributions summary:Matthew primarily contributed to enhancing the cuDF GPU DataFrame Library, focusing on improving functionality related to data manipulation and indexing. Their work involved addressing bugs in DataFrame reindexing, optimizing data structures, and implementing new APIs. Furthermore, they demonstrated skills in data analysis by modifying the Series API to better align with pandas behavior.
cudfdataframegpurapidsarrow
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