Michal Malohlava
VP Of Engineering at H2O.ai
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMichal Malohlava is a VP of Engineering at H2O.ai with 13 years of experience building and scaling AI and data platforms from core product architecture to production delivery. He progressed from software engineer and chief architect roles to lead engineering growth at a fast-moving AI cloud company, driving work on flagship projects like H2O and Sparkling Water. Hands-on background in backend and DevOps is reflected in notable open-source contributions—improving build pipelines, cross-platform CI, and versioning for the popular h2oai/datatable project. He holds advanced academic credentials in software engineering (MSc and PhD work) and combines rigorous research roots with pragmatic system-building. Based in Mountain View, he blends deep technical craft with leadership in deploying AI tooling at scale.
13 years of coding experience
5 years of employment as a software developer
Mgr (MSc. software engineering), Computer Science, Software Engeneering, Mgr (MSc. software engineering), Computer Science, Software Engeneering at Univerzita Karlova v Praze, Matematicko-fyzikální fakultaGMK Bilovec
English, French, Czech
Stackoverflow
437reputation
17kreached
25answers
1question
Github Skills (22)
docker10
spark10
back-end-development10
big-data10
dockers10
cicd10
scala10
h2o10
build-automation10
jenkins10
jenkins-ci10
python9
performance-analysis8
machine-learning8
performance-monitor8
Programming languages (9)
Github contributions (5)
h2oai/sparkling-water
Oct 2014 - Aug 2020
Sparkling Water provides H2O functionality inside Spark cluster
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 1272 commits, 232 PRs in 5 years 11 months
Contributions summary:Michal's commits focus on core aspects of the Sparkling Water project, including changes in H2OContext and H2OConf classes that directly interact with the H2O functionality within the Spark cluster. The code changes involve modifications to the core functionality. In addition, the code is related to H2O cloud building for usage in Spark cluster.
sparkh2omachine-learningintegrationpysparkling
h2oai/datatable
Jun 2017 - Jan 2020
A Python package for manipulating 2-dimensional tabular data structures
Role in this project:DevOps Engineer
DevOps EngineerContributions:1 review, 56 commits, 44 PRs in 2 years 7 months
Contributions summary:Michal primarily focused on enhancing the build and deployment infrastructure of the `datatable` repository. They modified the `setup.py` script to include versioning and build suffixes, along with making various improvements to the Jenkinsfile, including setting up coverage reports for OSX and Linux. Furthermore, the user refactored the build pipeline to support multiple targets and platforms, and addressed several issues related to dependency management.
data-structuredata-structurespythondata-analysisperformance
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