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Design RAG Evaluation and Debugging

Last updated: Jun 22, 2026

Quick Overview

This question evaluates a candidate's ability to design evaluation and debugging frameworks for production RAG systems, testing practical ML engineering skills in retrieval-augmented generation pipelines. It assesses system design competency around offline and online quality metrics, regression detection, and failure localization in high-stakes domains requiring strict data permissions and faithfulness guarantees.

  • medium
  • Plaid
  • ML System Design
  • Machine Learning Engineer

Design RAG Evaluation and Debugging

Company: Plaid

Role: Machine Learning Engineer

Category: ML System Design

Difficulty: medium

Interview Round: Onsite

Quick Answer: This question evaluates a candidate's ability to design evaluation and debugging frameworks for production RAG systems, testing practical ML engineering skills in retrieval-augmented generation pipelines. It assesses system design competency around offline and online quality metrics, regression detection, and failure localization in high-stakes domains requiring strict data permissions and faithfulness guarantees.

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|Home/ML System Design/Plaid

Design RAG Evaluation and Debugging

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Plaid
Jun 19, 2026, 12:00 AM
mediumMachine Learning EngineerOnsiteML System Design
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