Design a Short-Video Recommendation System
Company: Meta
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Technical Screen
Overview: This question evaluates competency in designing large-scale short-video recommendation systems, including machine learning model selection, candidate generation and ranking, real-time personalization, feedback signal design, evaluation metrics, latency and scalability constraints, cold-start handling, exploration–exploitation trade-offs, and safety/abuse controls. It is commonly asked in the ML system design domain to assess system-level machine learning engineering and product-aware architectural thinking, and it combines conceptual understanding with practical application by requiring both high-level trade-off reasoning and concrete serving and evaluation considerations.