Design a Lens Recommendation System
Company: Snapchat
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Onsite
Quick Answer: This question evaluates a candidate's understanding of end-to-end machine learning recommendation system design for augmented-reality lenses, covering product goals and success metrics, candidate generation and ranking, training data/labels/features, online serving and feedback loops, cold-start handling, use of weighted logistic regression for differing engagement values, and feature/model platform capabilities. It is commonly asked in ML System Design interviews to assess both conceptual understanding and practical application of production recommender systems, emphasizing scalability, evaluation metrics, data-driven modeling, and engineering trade-offs within the machine learning and recommender systems domain.