Compare NLP tokenization and LLM recommendations

Company: Google

Role: Machine Learning Engineer

Category: Machine Learning

Difficulty: medium

Interview Round: Onsite

Quick Answer: This question evaluates a candidate's understanding of NLP tokenization approaches and the ability to design LLM-based recommendation components, assessing competencies in trade-offs among word/character/subword tokenization, OOV and multilingual handling, and roles LLMs can play in recommendation pipelines.