Improve and debug the shopping app

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Quick Overview

This question evaluates product-minded engineering competencies including product intuition, user-experience assessment, telemetry-driven diagnostics, funnel and segmentation analysis, and debugging/observability skills relevant to a machine learning engineer.

Improve and debug the shopping app

Company: Whatnot

Role: Machine Learning Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

You are evaluating a live-shopping mobile app from a product-minded engineering perspective. Answer the following as one integrated exercise: 1. What do you think of the app experience, and what improvements would you suggest? 2. How would you identify product categories that are underperforming? 3. Suppose the team believes there is a bug affecting category performance or user experience. How would you debug it? Your answer should explain how you would combine direct hands-on use of the app, product intuition, metrics, dashboards, logs, funnels, segmentation, and hypothesis-driven investigation.

Overview: This question evaluates product-minded engineering competencies including product intuition, user-experience assessment, telemetry-driven diagnostics, funnel and segmentation analysis, and debugging/observability skills relevant to a machine learning engineer.

Read the full Whatnot Machine Learning Engineer interview experience this question came from

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Whatnot
Jan 17, 2026
mediumMachine Learning EngineerTechnical ScreenSystem Design
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You are evaluating a live-shopping mobile app from a product-minded engineering perspective.

Answer the following as one integrated exercise:

  1. What do you think of the app experience, and what improvements would you suggest?
  2. How would you identify product categories that are underperforming?
  3. Suppose the team believes there is a bug affecting category performance or user experience. How would you debug it?

Your answer should explain how you would combine direct hands-on use of the app, product intuition, metrics, dashboards, logs, funnels, segmentation, and hypothesis-driven investigation.

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