Andrew Nitu
Senior Software Engineer at LiveKit
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAndrew Nitu is a Senior Software Engineer in San Francisco with nine years of hands-on experience building cloud-native infrastructure and ML platforms. He has shipped production systems at Databricks—spanning Kubernetes cluster orchestration, Go operators, Scala services, and provisioning tooling—and now contributes to LiveKit’s engineering efforts. As an early MLflow contributor, he improved autologging for LightGBM and XGBoost, adding schema inference and example capture that make model reproducibility and observability more robust. His background includes building auto-remediation frameworks, training observability features, and performance-focused tooling across backend and frontend stacks, reflecting a pragmatic focus on reliability and developer productivity. Collected internships from startups to enterprise taught him to move quickly from prototype to scalable systems while keeping developer experience front of mind.
9 years of coding experience
6 years of employment as a software developer
William Lyon Mackenzie Collegiate InstituteBachelor of Computer Science, Bachelor of Computer Science at University of Waterloo
Github Skills (9)
xgboost10
machine-learning10
mlflow10
python10
lightgbm10
testing8
pytest8
pandas7
yaml5
Programming languages (6)
Github contributions (5)
mlflow/mlflow
Sep 2020 - Nov 2020
Open source platform for the machine learning lifecycle
Role in this project:
ML Engineer
ML EngineerContributions:56 reviews, 10 commits, 25 PRs in 2 months
Contributions summary:Andrew primarily contributed to the autologging functionality of the MLflow library, focusing on the LightGBM and XGBoost integrations. Their work involved adding features such as input/output schema inference and input example collection for the autologged models. Additionally, they addressed bugs and improved the robustness of existing autologging features for these popular machine learning frameworks. Furthermore, the user made documentation updates to clarify autologging behavior and usage.
pythonlifecyclemlmachine-learningincremental-learning
andrewnitu/mlflow
Sep 2020 - Nov 2020
Open source platform for the machine learning lifecycle
Contributions:1 review, 1 PR, 200 pushes in 2 months
pythonlifecyclemachine-learningmodel-managementdvc
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