Aaron Stern is an applied ML scientist and engineer with 13 years of experience translating research into production systems, currently working on prediction and planning for the Waymo Driver in Berkeley. He has led ML-driven product work across startups and research labs, including building ordering-efficiency models as Tech Lead at Afresh and developing AI features and evaluation pipelines for assistant agents at Harvey. Aaron holds a PhD in Computational Biology from UC Berkeley and began his career blending computational biology research with machine learning at GRAIL, giving him a strong foundation in data-driven problem solving. He is skilled at moving models from prototype to operational impact in high-stakes domains like autonomous vehicles and grocery supply chains. A less obvious strength is his ability to bridge deep academic training with hands-on engineering leadership, making him effective at both designing novel algorithms and shipping robust systems.
13 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Statistics, 4.0, Bachelor of Science - BS, Computer Science, Statistics, 4.0 at Brigham Young University
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