Summary
Phil Gaudreau is a Senior Staff Data Scientist with 11 years of experience and a Ph.D. in Computational and Applied Mathematics, currently building trigger-driven, agentic AI systems at Cisco Meraki to automate self-troubleshooting and self-healing networks. He has a track record of scaling large production ML systems—from LinkedIn capacity-forecasting and anomaly-detection pipelines that saved millions and sped hyperparameter tuning thousands-fold, to Bosch-wide forecasting of millions of time series—combining PyTorch, Spark, Kubernetes, Snowflake, and cloud migrations. Phil co-led the Ambient Agents Framework, a globally used platform for closed-loop remediation, and brings particular strength in word embeddings, meta-learning, and practical causal inference (DML) at scale. He thrives at the intersection of research and production, turning advanced algorithms into reliable, observable services and unifying schemas and tooling to streamline cross-team collaboration. Based in Mountain View, he blends deep mathematical rigor with hands-on engineering and an unusual habit of turning small simulation or research gains into sizable production wins.
11 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computational and Applied Mathematics with a Certificate in Data Science, Doctor of Philosophy (Ph.D.) Computational and Applied Mathematics with a Certificate in Data Science at University of Alberta
French, English