Eugene Yan

       

Hi, I'm Eugene Yan. I build recommendation systems and AI-powered experiences that serve customers at scale. I also write and speak about RecSys, LLMs, and engineering.

I'm a Principal Applied Scientist at Amazon where I built real-time retrieval, bandit rankers, and recsys in search (see RecSys 2022 keynote). Currently, I'm building AI-powered experiences and systems for summarization, translation, Q&A, etc.

Previously, I led the machine learning team at Alibaba/Lazada where I also built product ranking (conversion & revenue up 5-20%), push-notifications (CTR & add-to-cart up 10%), product & review classification (cost down 90%), and more.

As an early hire in a healthtech Series A, I led the team to ship an ML system for Southeast Asia's largest healthcare provider. At IBM, I built job forecasts & recommendations.

Outside of work, I share the ghost knowledge of applying machine learning, lessons from applying LLMs, and host a weekly AI Paper Club. I'm also an operator-angel in data, ML, and infra startups, and 🏂 and 🥾⛰️ in Seattle.

2020 - now: Principal Applied Scientist @ Amazon

(RecSys, LLMs, Engineering)


2018 - 2019: ML Lead @ Healthtech Series A (Disease Detection, Cost Estimation)


2017 - 2018: VP, Data Science @ Alibaba (E-Commerce Machine Learning Systems)


2015 - 2017: Data Scientist @ Lazada (Ranking, ML Automation, MLOps)


2013 - 2015: Data Scientist @ IBM (Workforce Analytics, Fraud Detection)

AIterate LabsHow I can help READMEI read everything but receive too much to respond to all of it.



Bio

Eugene Yan is a Principal Applied Scientist at Amazon building recommendation systems and AI-powered products that serve customers at scale. He's led ML/AI teams at Alibaba, Lazada, and a Healthtech Series A. He writes about RecSys, LLMs, and engineering at eugeneyan.com.

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