Kiyo Kunii
Machine Learning Engineer at Opera Tech
Tokyo, Japan
Summary
🤩
RockstarKiyo Kunii is a Machine Learning Engineer based in Tokyo with a decade of experience building production-ready data and ML systems. He contributes actively to prominent open-source projects in the Kedro ecosystem, improving backend code quality, documentation, testing, and pipeline orchestration—work that helps teams make data science workflows reproducible and maintainable. Comfortable across engineering and docs, he has added core pieces like KedroContext and fixed nuanced API documentation gaps such as HDFS3DataSet coverage. Kiyo combines practical software engineering discipline with hands-on ML-focused programming, and he pays attention to developer tooling and legal/quality checks that keep projects healthy. Quietly detail-oriented, he often surfaces behind-the-scenes improvements (e.g., test structure refactors and license verifications) that reduce long-term maintenance friction.
10 years of coding experience
Stackoverflow
582reputation
16kreached
10answers
12questions
Github Skills (14)
kedro10
api-documentation10
python10
testing9
data-visualization9
data-visualisation9
data-visualizations9
git9
data-engineering8
pipeline8
juniper6
google-cloud-platform6
nodes6
tfrecord6
Programming languages (9)
Github contributions (5)
kedro-org/kedro
May 2019 - Sep 2021
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Role in this project:
Backend Developer & Documentation Specialist
Backend Developer & Documentation SpecialistContributions:20 reviews, 123 commits, 62 PRs in 2 years 4 months
Contributions summary:Kiyo primarily contributed to the codebase by fixing API documentation and adding missing API documentation for the `HDFS3DataSet`. They also added and integrated the `KedroContext` class. Additionally, the user made modifications to the project's testing framework and structure, and refactored codebase elements.
experiment-trackingpythonsciencepipelinedata-science
kedro-org/kedro-viz
Jul 2019 - Oct 2020
Visualise your Kedro data and machine-learning pipelines and track your experiments.
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 release, 22 reviews, 29 commits in 1 year 3 months
Contributions summary:Kiyo primarily focused on improving code quality and adding features to the project. They removed smart quotes across multiple files, enhancing code consistency. The user also added legal header checks, implementing a tool to verify the presence of legal headers in Python files and ensuring the LICENSE.md file has correct content. Additionally, they pinned and later unpinned the pip version.
experiment-trackingpythonreactkedro-plugindata-science
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