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Design Comment Prediction Ranking System

Last updated: Jun 29, 2026

Quick Overview

This question evaluates proficiency in end-to-end machine learning system design for predicting user engagement, specifically the probability of a user commenting given exposure, covering problem formulation, label and feature engineering, model architecture, training and evaluation pipelines, low-latency serving, and operational concerns like monitoring and cold-start. It falls under the ML System Design / Machine Learning Engineering domain and is commonly asked to assess an engineer's ability to build scalable, bias-aware, low-latency ranking signals that integrate into multi-objective recommenders, with a primarily practical system-level focus rather than purely theoretical modeling.

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

Design Comment Prediction Ranking System

Company: Reddit

Role: Machine Learning Engineer

Category: ML System Design

Difficulty: medium

Interview Round: Technical Screen

Quick Answer: This question evaluates proficiency in end-to-end machine learning system design for predicting user engagement, specifically the probability of a user commenting given exposure, covering problem formulation, label and feature engineering, model architecture, training and evaluation pipelines, low-latency serving, and operational concerns like monitoring and cold-start. It falls under the ML System Design / Machine Learning Engineering domain and is commonly asked to assess an engineer's ability to build scalable, bias-aware, low-latency ranking signals that integrate into multi-objective recommenders, with a primarily practical system-level focus rather than purely theoretical modeling.

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|Home/ML System Design/Reddit

Design Comment Prediction Ranking System

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Reddit
Jun 4, 2026, 12:00 AM
mediumMachine Learning EngineerTechnical ScreenML System Design
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