Mateusz聽Dymczyk
Software Engineer, Machine Learning at Meta
London, England, United Kingdom
Summary
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Rockstar馃帗
Top SchoolMateusz Dymczyk is a software engineer and machine learning practitioner with 14 years of experience building scalable backend and data engineering systems across startups and hyperscale companies. Currently at Meta working on Business Integrity for WhatsApp, he applies distributed-systems expertise and ML to combat spam, scams and fraud. He has deep JVM experience (Java, Scala), strong Python and Go skills, and recent hands-on C/CUDA work on multi-GPU ML libraries鈥攂ringing production-grade performance tuning to model engineering. At H2O.ai he led a small team on interpretability and contributed to widely used open-source projects like H2O-3 and Sparkling Water, adding SSL/TLS support and key integrations between Spark and H2O. Comfortable in both heavy and agile environments, he repeatedly bridges research and production: shipping core platform fixes, implementing distributed K-Means and FFM, and improving tooling for model deployment. An active community member who has led a Google Developer Group chapter, he prefers collaborating with passion-driven teams and contributing to open-source ecosystems.
14 years of coding experience
9 years of employment as a software developer
M.Sc. Eng., Applied Computer Science, 5, M.Sc. Eng., Applied Computer Science, 5 at Akademia G贸rniczo-Hutnicza im. Stanis艂awa Staszica w KrakowieLevel A2 of CEFR, Japanese Language, Level A2 of CEFR, Japanese Language at The Naganuma School in TokyoInformation Systems and Networks, Information Systems and Networks at ECE Paris
Polish, English, Japanese
Stackoverflow
15,061reputation
1.9mreached
326answers
67questions
java
top-1%
tomcat
top-5%
jsf
top-5%
algorithm
top-5%
apache
top-5%
scala
top-5%
Github Skills (33)
apache-spark10
spark10
integrate10
back-end-development10
machine-learning10
integrations10
java10
scala10
javas10
h2o10
apache9
ssl9
tls129
algorithm9
tls139
Programming languages (5)
Github contributions (5)
h2oai/h2o-3
Aug 2016 - Nov 2018
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:103 commits, 36 PRs, 162 pushes in 2 years 3 months
Contributions summary:Mateusz primarily focused on improving the H2O-3 machine learning platform's back-end functionality, demonstrated by code changes involving the `ClusteringUtils`, `KMeansModel`, and `ClusteringModel` classes. They contributed to the platform's security by adding SSL/TLS authentication and data encryption. Furthermore, the user addressed specific feature enhancements, such as modifying the default threshold method for models, and fixing an issue with the MOJO for SVM implementation.
xgboostgampythonk-meansautoencoders
h2oai/sparkling-water
May 2016 - Aug 2017
Sparkling Water provides H2O functionality inside Spark cluster
Role in this project:Back-end Developer
Back-end DeveloperContributions:74 commits, 38 PRs, 122 pushes in 1 year 3 months
Contributions summary:Mateusz primarily contributed to the Sparkling Water project by addressing core issues related to Spark cluster functionality and H2O integration. Their work involved fixing launch scripts for Spark cloud deployments and implementing necessary methods within the H2OSparkListener trait to ensure compatibility. They also addressed CSS issues within the Scala editor and removed duplicate classes, indicating involvement in UI and core functionality improvements. Further contributions included providing support for Spark SVM model support.
develapiintegrationrsparklingh2o
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