Tomas Nykodym is a seasoned software engineer with 13 years of experience building distributed data and machine learning platforms, currently contributing to Databricks in San Francisco. His career includes five years helping develop a distributed analytics platform at 0xDATA and continued focus on scalable ML infrastructure since joining Databricks in 2017. Trained in computer security and computer engineering in Prague and at SUNY Binghamton, he blends systems-level rigor with practical product delivery. Known for working at the intersection of large-scale data processing and applied ML, he brings deep experience in making complex distributed systems reliable and performant. An engineer who transitioned from European graduate training to Bay Area production systems, he pairs academic breadth with hands-on platform-building chops.
13 years of coding experience
5 years of employment as a software developer
Master's degree, Computer Engineering, Master's degree, Computer Engineering at Czech Technical University in Prague
Computer security, Computer security at State University of New York at Binghamton
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.
Contributions:1259 commits, 97 PRs, 1309 pushes in 3 years 5 months
xgboostgampythonk-meansautoencoders
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.