Rachel Hu is a founder and AI leader with 7 years of experience building production-grade machine learning systems and startups in the Bay Area. As Cofounder and CEO of Energent.ai (and CambioML), she focuses on no-code, transparent automation that brings controllable AI to private desktops. Previously an applied scientist at AWS AI, she helped build LLMs, contributed to highly starred open-source ML projects, and co-authored content used by 100k+ monthly learners. Her background blends rigorous ML research and teaching (Berkeley, Northwestern) with quantitative finance and enterprise NLP experience, giving her a rare mix of product, research, and industry-savvy engineering. A Y Combinator alumna with degrees in ML/statistics and financial engineering, she frequently translates complex models into actionable, auditable workflows. An understated strength: she leverages academic teaching experience to make sophisticated AI approachable for nontechnical users.
7 years of coding experience
6 years of employment as a software developer
Master's degree Machine Learning and Statistics, Master's degree Machine Learning and Statistics at University of California, Berkeley
Y Combinator
Bachelor’s Degree Double Financial Engineering & Statistics, Bachelor’s Degree Double Financial Engineering & Statistics at University of Waterloo
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