Design Feed Ranking and HTML Generation
Company: Figma
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Onsite
Overview: This question evaluates the ability to design end-to-end machine learning systems for personalized feed ranking and for natural-language-to-HTML generation, testing competencies in objectives setting, candidate generation and ranking, feature engineering, cold-start handling, exploration, online serving, offline and online evaluation, data collection, model architecture, supervised fine-tuning, reinforcement learning or preference optimization, safety constraints, and the use of LLMs for judging. It is commonly asked to probe architectural trade-offs, scalability and production operational considerations, falls under the ML System Design and applied machine learning domain, and assesses both conceptual understanding of high-level design and practical application knowledge for production implementation.
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