How to Architect a Personalized Ads Serving System
Company: Upstart
Role: Data Scientist
Category: Machine Learning
Difficulty: hard
Interview Round: Technical Screen
##### Scenario
You are asked to architect a full-funnel advertising platform that serves personalized ads to users on a social media app.
##### Question
Design an ads serving system end-to-end. Cover data collection, feature engineering, model choice, real-time ranking, feedback loops, and A/B evaluation. What offline and online metrics would you track and how would you handle cold-start users?
##### Hints
Think retrieval → ranking → re-ranking, latency budgets, feature stores, and exploration/exploitation strategies.
Quick Answer: This question evaluates a data scientist's competency in designing end-to-end personalized advertising systems within the Machine Learning domain, covering system-level ML architecture, feature engineering and stores, multi-stage model pipelines, real-time serving, experimentation, and evaluation under latency and scale constraints.