How do I approach ML System Design interview questions?

ML System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master ml system design interviews.

What difficulty level is this interview question?

This is a medium difficulty ML System Design question, commonly asked during Technical Screen rounds at Lyft.

What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at Lyft during technical interviews.

Design an HR Document AI Platform | Lyft Interview Question

Design an HR Document AI Platform

Last updated: Apr 2, 2026

Quick Overview

This question evaluates a candidate's competency in designing secure, compliant, and scalable ML-driven document ingestion, search, and question-answering platforms, testing skills in NLP retrieval, indexing, model serving, pipelines, access control, evaluation, monitoring, and privacy-preserving architecture.

Lyft

Mar 12, 2026, 12:00 AM

Machine Learning Engineer

Technical Screen

ML System Design

Design an internal AI platform for a bank's HR organization. The platform should ingest HR documents such as policies, benefits guides, onboarding manuals, and compliance documents, then let employees search the corpus, ask natural-language questions, and receive answers with source citations. Describe the functional requirements, security and privacy requirements, document ingestion pipeline, indexing and retrieval design, model serving flow, access control, evaluation strategy, monitoring, and scaling considerations.

Solution

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