Mike Bernico
GenAI Agentic Data Lead
Benicia, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMike Bernico is a machine learning leader with 11+ years of experience shaping GenAI, synthetic data, and agent architectures across Google and DeepMind. He designs RL-driven datasets and systems that turn LLMs into multi-step, tool-using agents, and led enterprise-wide synthetic data strategies that materially expanded pretraining corpora with privacy-preserving techniques. Mike has productionized edge ML—deploying TensorFlow Lite Micro models to wearable devices—and built planet-scale agent memory and AutoRater systems for personalized, evaluable LLM experiences. His background spans applied research, engineering leadership, and teaching, and he’s an active open-source contributor (notably to boruta_py) who blends academic rigor with product impact. Based in Benicia, CA, he’s also a published author and former adjunct instructor committed to fairness and reducing bias in ML. Colleagues describe him as a practical innovator who connects reinforcement learning research to deployable data infrastructures.
11 years of coding experience
22 years of employment as a software developer
Master of Science (MS), Computer Science, Master of Science (MS), Computer Science at University of Illinois Springfield
English
Github Skills (9)
scikit-learn10
machine-learning10
random-forest10
python10
data-science10
feature-selection10
scikit10
numpy7
pandas7
Programming languages (4)
Github contributions (5)
scikit-learn-contrib/boruta_py
Apr 2016 - Oct 2016
Python implementations of the Boruta all-relevant feature selection method.
Role in this project:
Data Scientist
Data ScientistContributions:8 commits, 2 PRs, 5 comments in 6 months
Contributions summary:Mike primarily contributed to the development and maintenance of the `boruta_py` Python package, which implements the Boruta feature selection method. Their contributions included initial package setup, refactoring core components, adding examples (using the scikit-learn RandomForestClassifier), and fixing reported issues. The user demonstrated a focus on applying Boruta to the Madalon dataset and ensuring the package's functionality and usability.
implementationspythonmethodscikit-learnselection
mbernico/CS570
Feb 2015 - Mar 2017
Contributions:43 commits, 1 PR, 43 pushes in 2 years 1 month
pythonsciencedata-sciencemachine-learningpandas
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