Jiří Klein is a Forward Deployed Applications engineer with seven years of experience building production-ready data and ML infrastructure across consultancy and carbon-tech startups. He progressed from forensic data analyst to senior roles at QuantumBlack and BeZero Carbon, combining hands-on engineering leadership with practical deployment of data pipelines. An active contributor to the popular Kedro project, Jiří has deep MLOps and back-end expertise—refactoring core dataset components and improving async pipeline reliability for real-world Spark/Databricks environments. Trained in engineering mathematics from the University of Bristol and Czech Technical University, he blends rigorous quantitative thinking with product-focused execution. Based in England, he brings a pragmatic mix of research-grade technical skill and delivery experience in high-stakes, data-driven organisations.
7 years of coding experience
9 years of employment as a software developer
High School Bilingual and Multilingual Education, High School Bilingual and Multilingual Education at Gymnázium Olomouc - Hejčín
Mathematical Engineering, Mathematical Engineering at Czech Technical University in Prague
Master’s Degree Engineering Mathematics, Master’s Degree Engineering Mathematics at University of Bristol
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:
Back-end Developer & MLOps Engineer
Contributions:6 reviews, 19 commits, 1 PR in 7 months
Contributions summary:Jiří primarily focused on improving the `kedro` library's functionality related to data pipelines, specifically addressing hook synchronization within asynchronous node execution and refactoring core components like `SparkHiveDataSet`. The user also addressed bug fixes, including pandas.DataFrame support in `YAMLDataSet` and implementing a fix for `VersionedDataset` within the Databricks environment. The contributions also included refactoring and improvements to configuration loading and pipeline packaging processes within the `kedro` framework, alongside documentation updates.
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