GEORGE LU

Product Manager, AI/ML & Recommendation Systems

About

Seasoned Product Manager with 8 years of experience building and scaling high-stakes AI systems at a billion-user scale, specializing in recommendation engines, search relevance, and algorithmic interpretability. Proven track record of driving products from 0-1 to market, generating over $100M+ ARR, and currently leading user signal innovation for Facebook Reels. Expertly translates complex human intent into explicit ranking signals to create user-steerable systems that deliver meaningful control and significant business impact.

Work

Meta
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Product Manager

Summary

Spearheaded product strategy and execution for Facebook Reels, focusing on user feedback, AI transparency, and global content discovery to enhance engagement and personalization for billions of users.

Highlights

Defined and owned the strategic roadmap for Facebook Reels' explicit user feedback signals portfolio, consistently driving topline wins on app sessions through highest-weighted ranking features.

Led the 0→1 strategy and execution of "Tune Your Algo," an AI-powered transparency product that empowered users with direct control over Reels ranking, navigating complex ML, policy, and design alignment.

Launched Facebook Reels Explore globally from 0→1, providing a personalized discovery surface that enabled billions of users to actively explore interests beyond algorithmic feeds.

Indeed
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Product Manager

Summary

Directed personalized search ranking strategy and product development for Indeed's core products, leveraging ML and data science to significantly improve jobseeker outcomes and reduce complaints.

Highlights

Defined and led personalized search ranking strategy across Indeed's core products, shipping a negative preference collection flow that reduced jobseeker complaints by 75%.

Drove a systematic experimentation roadmap spanning ML model tuning and explainability, increasing global jobseeker positive outcomes by 10% and sponsored applies by 5%.

Led the 0→1 development and cross-company alignment for the Match Engine, a centralized real-time scoring platform evaluating billions of jobseeker-job pairs daily.

Indeed
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Product Manager (Assessments)

Summary

Developed and executed growth strategies for Indeed's Assessments product, significantly improving hiring efficiency and reducing employer friction through strategic feature development and international expansion.

Highlights

Defined and executed growth strategy for the Assessments product, reducing enterprise employers' average time to hire by 12% and increasing jobseeker callback likelihood by 20%.

Led international expansion of Assessments to 21 new countries, increasing employer opt-in by 42% and jobseeker-completed assessments by 10x through strategic A/B testing.

Shipped a self-serve assessment resend feature, eliminating a key source of employer friction and reducing customer service tickets by 93%.

Education

University of Michigan Ann Arbor
Ann Arbor, Michigan, United States of America

B.S.

Information Analysis

Grade: 3.8/4.0

Courses

Minor in Computer Science

Languages

English

Skills

AI/ML Product Development

AI/ML Product Development.

Ranking and Recommendation Systems

Ranking and Recommendation Systems.

LLMs

LLMs.

Personalization

Personalization.

Large-Scale Experimentation

Large-Scale Experimentation.

SQL

SQL.

Python

Python.

GEORGE LU