This question evaluates skills in designing end-to-end ML systems for personalization from free-text feedback, covering competencies in NLP feature representation (embeddings), data modeling, retrieval, pipeline orchestration, model selection, and scalability within the ML System Design domain.
You are building an embeddings + personalization pipeline for a consumer product (e.g., genealogy/ancestry). Users provide free-text feedback (comments, reviews, support tickets) about products/features.
Design a system that:
Assume moderate scale (millions of users, tens of millions of feedback records). Discuss data model, pipelines, model choices, retrieval, updates, and evaluation.