Pinterest Interview Questions (2026)

37 questions · 58 experiences · InterviewDB (33) · 1p3a_oj (30) · LeetCode (23) · 1p3a (8) · Reddit (1)

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Pinterest Machine Learning Engineering Internship Online Test Overview

1p3a MLE
FREE Oct 2025 Question

Pinterest Coding 2024, Can't solve using AI either

LeetCode SWE
FREE Mar 2025 Question

Pinterest | Phone Screen | Backend Engineer

LeetCode Backend Los Angeles
🔒 Dec 2024 Question

Pinterest | Internship | Dublin | Nov 2024 [Reject]

LeetCode SWE Dublin
🔒 Nov 2024 Question

Pinterest | Onsite | Bay Area | Meeting rooms variation

LeetCode SWE Bay Area
🔒 Jul 2024 Question

Pinterest | Software Engineer L14| Phone Screen

LeetCode SWE USA
🔒 Apr 2024 Question

Pinterest + Meta L4 offers - My journey and advice

Reddit Data Eng
FREE Feb 2024 Question

Pinterest | Onsite | Rejected | June 2022

LeetCode SWE USA
🔒 Jul 2022 Question

Pinterest | Data Analyst Interview | Reject

LeetCode SWE Los Angeles
🔒 Jul 2020 Question

Implement a Sparse Matrix Class (store/print/add/multiply)

1p3a_oj SWE
🔒 Question

Weighted Job Scheduling for Maximum Profit Without Overlaps

1p3a_oj SWE
🔒 Question

Top K Scored Pins Retrieval by Type Data Structure

1p3a_oj SWE
🔒 Question

Find Shortest Path Between Products

1p3a_oj SWE
🔒 Question

Minimum Copies of a String

1p3a_oj SWE
🔒 Question

Determine Relatedness and Shortest Distance Between Pins

1p3a_oj SWE
🔒 Question

Implement custom round function

1p3a_oj SWE
🔒 Question

Longest Substring with Repeated Character

1p3a_oj SWE
🔒 Question

Naive Bayes Implementation

1p3a_oj SWE
🔒 Question

Delete Node in a Linked List

1p3a_oj SWE
🔒 Question

Minimize Result by Adding Parentheses to Expression

1p3a_oj SWE
🔒 Question

Grant Access (permissions propagation / access control)

1p3a_oj SWE USA
🔒 Question

#322 Coin Change

LeetCode SWE
🔒 Question

#1244 Design A Leaderboard

LeetCode SWE
🔒 Question

#465 Optimal Account Balancing

LeetCode SWE
🔒 Question

#410 Split Array Largest Sum

LeetCode SWE
🔒 Question
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Pinterest Interview Process Overview

The Pinterest interview process typically includes a recruiter screen, one to two technical phone screens, and a 4-6 round on-site or virtual on-site loop. Each round serves a distinct calibration purpose: coding rounds measure correctness, code quality, and complexity reasoning; system design rounds measure architectural judgment at the appropriate level; behavioral rounds measure ownership, leadership scope, and collaboration. Reports tagged on LeakCode from 2024-2026 show Pinterest runs a calibrated process consistent with industry norms for companies of its tier.

Difficulty calibration: Pinterest coding rounds typically run medium difficulty with follow-up depth as the senior discriminator. System design rounds expect production-grade trade-off articulation at L4+ levels. Behavioral rounds expect quantified outcomes ("reduced p99 latency from 800ms to 120ms") rather than vague impact claims. The candidates who advance consistently demonstrate clear thinking out loud rather than perfect final answers.

How To Use Pinterest Question Reports

Real candidate-reported interview questions are a calibration tool, not a memorization target. Pinterest updates its question pool every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage approach: identify the patterns that appear repeatedly in Pinterest reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.

Filter the questions above by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Pinterest's pool. Reports tagged with quantified difficulty and explicit round type are higher-signal than reports without those tags. The metadata filters help you build a focused study plan in 1-2 hours rather than 8-10 hours of unstructured browsing.

Common Pinterest Interview Mistakes

Reports tagged "no hire" at Pinterest consistently surface a few patterns: jumping into code without clarifying requirements, coding silently for extended periods, missing edge cases (empty input, single element, large input, overflow), producing working code the candidate cannot refactor when probed, and behavioral stories that use "we" instead of "I" diluting individual signal. Strong candidates explicitly avoid these patterns by following a consistent round template.

The single most predictive failure mode in recent reports: not asking clarifying questions. Interviewers are explicitly trained to weight this dimension. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into implementation immediately. Strong candidates also verbalize their approach before writing code; weak candidates code in silence and lose the communication dimension of the round's calibration.