Design a Short-Video Recommendation System

Q: How do I approach ML System Design interview questions?

ML System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master ml system design interviews.

Q: What difficulty level is this interview question?

This is a medium difficulty ML System Design question, commonly asked during Technical Screen rounds at Meta.

Q: What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at Meta during technical interviews.

Question

Design a Short-Video Recommendation System

PracHub · Accepted Answer

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.

Design a Short-Video Recommendation System

Quick Overview

Design a Short-Video Recommendation System

Submit Your Answer to Earn 20XP