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Scale AI Interview Guide

~28% easy, 56% medium, 15% hard. HackerRank OA problems can be hard (BFS-based reverse routing reported). Live rounds involve multi-part production-style questions. · 16 tracked problems · Arrays, Strings, Dynamic Programming

Overview

Scale AI interviews blend standard algorithm questions with data infrastructure problems. The HackerRank OA is the first gate — problems can include binary search variants and recursive problem decomposition that are trickier than they first appear. Scale's engineering work centers on data pipelines, labeling infrastructure, and ML ops. System design questions reflect this — expect to design annotation workflows, quality assurance pipelines, and data processing systems at scale. The coding bar is solid but not extreme. Focus on clean implementations of medium-difficulty problems.

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Keep the editorial context on this page, then review the Scale AI problem set so the next rep stays tied to the interview you are targeting.

Interview Process

Timeline: 3-5PythonGoTypeScriptReact
RoundTypeDurationDescription
HackerRank OACoding90 minTimed problems, binary search and recursion variants
Phone ScreenCoding45 minMedium coding problem
Onsite (4-5 rounds)Mixed60 minCoding, system design, and data infrastructure

HackerRank OA, then phone screen, followed by 4-5 onsite rounds: coding, system design, and domain-relevant data infrastructure discussions. Timeline is 3-5 weeks.

Difficulty Breakdown

28% easy
56% medium
15% hard

56% medium, 28% easy, 15% hard is moderate. The challenge is domain-specific system design rather than algorithmic difficulty.

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Curated by Leo Kwan

This guide is AI-assisted editorial, reviewed and fact-checked by Leo. Interview data is aggregated from public sources — not scraped or copied. Last updated 2026-04-03.

Sources

Interview data aggregated from public sources including LeetCode, Glassdoor, PracHub, Blind, and levels.fyi, as well as public company career pages, engineering blogs, and community interview reports.