EY

Eugene Yan

ML, Recsys, LLMs @ Amazon. Building to serve at scale; writing to learn & teach.

Seattle, Washington

Invests in

  • Min Investment:

    $5,000.00
  • Max Investment:

    $50,000.00
  • Target Investment:

    $25,000.00

Work Experience

2020

  • Senior Applied Scientist

    2022

    Building ML systems to serve customers at scale. Advising execs and teams on how to solve the right problems with the simplest solution. Educating the Org on ML, RecSys, LLMs. • Designing and shipping centralized LLM systems for new GenAI customer experiences: - Built and deployed guardrails (e.g., content-safety, factual inconsistency) for customer-facing apps. - Built retrieval, clustering, and caching systems, improving output & reducing cost by 80%. - Building finetuning pipeline for task-specific LLMs (e.g., summarization) to address legal/privacy concerns, eliminate dependency of 3rd-party APIs, improve performance, and reduce costs by 90%. - Led the use of LLMs to accelerate and nearly complete a three-year roadmap within a year. • Shipping ML & recommender systems to help customers discover, buy, and read more books: - Built bandit ranker to explore-exploit with sparse feedback; increased CTR XX% and profit $Y mil. - Designed labeling queues to collect ground-truth via strategies for precision, recall, coverage. • Educating & advising organizational leadership and teams as part of Generative AI Working Group.

  • Applied Scientist

    2020 - 2022

    • Built real-time candidate retrieval for recommendations and search; increased units and revenue by XX million, improved search metrics by Y%, 8,000+ queries/sec, p99 latency < 25ms, low cost (<2k monthly). • Prototyped interactive tag-based discovery for books; launched on Amazon detail page and Kindle app. • Incremental RecSys improvements: Added serendipity & book length preferences; +XX million in revenue.

  • Builder

    2021

    • Iterating on AI systems, amplifying teams: https://www.aiteratelabs.com • How to build successful LLM products: https://applied-llms.org • Papers, guides, and interviews with ML practitioners: https://applyingml.com

2018 - 2019

  • Machine Learning Lead

    2018 - 2019

    uCare.ai aims to make healthcare more efficient and reduce cost. Winner of Frost & Sullivan's 2019 Innovation Award and accredited by the Singapore government. Predicted chronic diseases with 80% recall & 50% precision. Wanted to work with insurers to improve insurees’ health & reduce claims; they wanted us to identify who was healthy to sell them more insurance. Shipped hospital bill prediction system for Southeast Asia’s largest healthcare provider; 60% model improvement over prior system,24/7 uptime, 99% SLA, sub-second latency (http://bit.ly/ucarexparkway). Also: pitching, hiring, ML strategy, community engagement, internal tooling (shortened dev cycle by 60%)

2015 - 2018

  • VP, Machine Learning

    2017 - 2018

    Lazada is Southeast Asia's largest e-commerce platform; acquired by Alibaba in April 2016. - Facilitated organizational & technological merger between Lazada and Alibaba. Built & led a team of 20+. Engaged execs on data & ML roadmap. Systems we shipped include: - Search and RecSys improvements: Increased CTR and conversion by ~30% - Push notifications: Increased open-rate and add-to-cart by 10%, reduced opt-out rate, increased DAU - Delivery forecasting: Migrated from R to Python and shortened model refresh cycle by 5x - Internal newsletter: Increased business’ understanding of ML, spurring more collaboration on projects

  • Senior Data Scientist

    2015 - 2017

    Built scalable ML systems across 6 countries, improving business outcomes and user experience, including: - Product ranking: Increased conversion by 5-8% and revenue by 15 - 20% - Product classifier: 95% top-3 accuracy, 200+ queries/second, reduced manual effort >95%, cost by >50% - Search intent API: Increased search CTR by 3-5%, 400+ queries/second - Review classifier: >95% precision, >85% recall, reduced manual effort and cost by >90%

2013 - 2015

  • Data Scientist

    2014 - 2015

    Job demand forecasting & internal job RecSys; reduced attrition, reduced compute time by 90%.

  • Data Analyst

    2013 - 2014

    Social media analytics for global brand, anti-money laundering for global bank, supply chain for IBM.

  • Trade and Investment Analyst

    2011 - 2013

    Negotiated the Trans-Pacific Partnership, Singapore-Taiwan FTA, and Singapore-India FTA review.

  • Research Assistant

    2008 - 2011

    Contributed to 2 academic papers and several conference presentations.

2009 - 2009

  • Entrepreneur-Intern

    2009 - 2009

    Set up 1-Caramel (a patisserie and café); broke even within 6 months.