David Chudzicki
AI Engineer at Amazon Web Services (AWS)
Greater Boston United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Chudzicki is an AI engineer and seasoned software leader with 14 years of experience building scalable ML and data systems across startups and cloud platforms, currently working at LightTable and serving as Director of Product Engineering at Coiled. With a strong academic foundation (MS from University of Chicago, BA from Swarthmore) he blends mathematical rigor and practical engineering to make complex models more interpretable and reliable. He has deep hands-on experience from Kaggle to AWS, co-founding a short-lived startup and contributing to prominent open-source projects like Dask and Hypothesis, where he improved testing primitives and developer ergonomics. David’s background in configuring reproducible environments (e.g., packaging XGBoost in Kaggle’s Docker images) and documenting tooling demonstrates a focus on developer experience as well as model quality. Based in Greater Boston, he also communicates ideas publicly through his technical blog, signaling a commitment to teaching and clarity beyond code.
14 years of coding experience
7 years of employment as a software developer
BA, Mathematics and Statistics, BA, Mathematics and Statistics at Swarthmore CollegeMS, Mathematics, MS, Mathematics at University of Chicago
Stackoverflow
1,409reputation
292kreached
11answers
28questions
Github Skills (24)
property-based-testing10
xgboost10
python10
r10
testing10
dask10
documentation10
data-science9
package-management9
dockers9
docker9
fuzzing9
machine-learning8
rstudio8
sphinx7
Programming languages (11)
Github contributions (5)
dask/dask
Apr 2020 - Dec 2024
Parallel computing with task scheduling
Role in this project:
Technical Writer
Technical WriterContributions:2 reviews, 5 PRs, 6 comments in 4 years 8 months
Contributions summary:David primarily contributed to the documentation of the Dask project. Their work included correcting typos in the documentation, specifically changing "double" to "times" and fixing "point" to "pointers." They added an LLM chatbot integration to the Dask documentation, which was subsequently reverted and then re-added with adjustments to usage limits and messaging. This demonstrates a focus on improving the user experience through documentation and integrating helpful tools.
pythonschedulingparallelnumpydask
Kaggle/docker-python
Mar 2015 - May 2015
Kaggle Python docker image
Role in this project:Data Scientist
Data ScientistContributions:21 commits, 6 PRs, 9 pushes in 2 months
Contributions summary:David's contributions primarily revolve around the installation and management of R packages, specifically focusing on the integration of XGBoost for machine learning within the Kaggle Docker environment. They added, removed, and re-added XGBoost, indicating experimentation and iteration with the package. Additionally, they set a CRAN repository and added a newline to an RProfile, which suggests the user is configuring the R environment within the Docker container.
kagglepythondocker-imagedata-sciencedocker
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