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Design a CPA system for ad bidding

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's competency in ML system design for online advertising, covering modeling conversion probability and value (e.g., CVR and conversion delay), bid computation, and operational challenges like delayed/attributed conversions, sparse data, and fraud mitigation.

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

Design a CPA system for ad bidding

Company: Apple

Role: Machine Learning Engineer

Category: ML System Design

Difficulty: medium

Interview Round: Technical Screen

You are designing an ads bidding/optimization system where advertisers care about **CPA (cost per acquisition)**. Describe how you would design a system to **optimize toward a target CPA** while still participating in an auction. Cover: - What the objective is (platform vs advertiser) and how CPA is defined. - What models you need (e.g., CVR, value, conversion delay). - How to compute bids from predictions (e.g., bid shading, target CPA control). - How you handle delayed/attributed conversions, sparse data, and fraud. - Offline evaluation and online A/B testing metrics for CPA systems.

Quick Answer: This question evaluates a candidate's competency in ML system design for online advertising, covering modeling conversion probability and value (e.g., CVR and conversion delay), bid computation, and operational challenges like delayed/attributed conversions, sparse data, and fraud mitigation.

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|Home/ML System Design/Apple

Design a CPA system for ad bidding

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Apple
Mar 1, 2026, 12:00 AM
mediumMachine Learning EngineerTechnical ScreenML System Design
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You are designing an ads bidding/optimization system where advertisers care about CPA (cost per acquisition).

Describe how you would design a system to optimize toward a target CPA while still participating in an auction.

Cover:

  • What the objective is (platform vs advertiser) and how CPA is defined.
  • What models you need (e.g., CVR, value, conversion delay).
  • How to compute bids from predictions (e.g., bid shading, target CPA control).
  • How you handle delayed/attributed conversions, sparse data, and fraud.
  • Offline evaluation and online A/B testing metrics for CPA systems.

Submit Your Answer to Earn 20XP

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