Baolei Li is a Staff Machine Learning Engineer with 11 years of experience building production AI systems and a PhD in Physics, currently shaping homepage recommendations at YouTube after leading AI platform efforts at LinkedIn. He specializes in unifying ML workflows and improving search, feed ranking, and career relevance at internet scale, with measurable impact on retention and business metrics through data mining and anomaly detection. A pragmatic backend contributor to projects like Apache Pinot’s Thirdeye integration, he blends deep research instincts with production engineering to deploy robust monitoring and alerting systems. Based in Cupertino, he pairs rigorous academic training and hands-on systems work, and is known for turning complex statistical problems into scalable platform features that accelerate model iteration.
Apache Pinot - A realtime distributed OLAP datastore
Role in this project:
Back-end Developer
Contributions:14 commits, 31 PRs, 24 pushes in 1 year
Contributions summary:Baolei primarily contributed to the `thirdeye-pinot` project, focusing on implementing and modifying backend functionalities. Their work involved refactoring existing code for metric rescaling and anomaly detection, as well as adding new features for anomaly function management, including cloning and activation/deactivation in batch. Further modifications were made for data transformation, and alert configuration enhancements.
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Baolei Li - Staff Machine Learning Engineer at YouTube