Design a Game Recommendation System
Company: Roblox
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Onsite
Quick Answer: This question evaluates proficiency in end-to-end machine learning system design for recommender systems, covering competencies such as candidate generation and ranking architecture, feature engineering for users/games/context/interactions, cold-start and long-tail handling, model selection and training objectives, offline and online evaluation, and deployment and monitoring. It is commonly asked to assess a candidate's ability to reason about scalable, production-grade recommendation pipelines and engineering trade-offs within the ML System Design domain, testing both conceptual understanding of system components and practical application of evaluation, serving latency, and iteration strategies.