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Pinterest interview notes, page 19 of 24

Large Enterprises

Most of these Pinterest write-ups come from Machine Learning Engineers (91), then Software Engineers (77) and Data Scientists (51). The most reported rounds are the technical phone screen (168), the system design round (37), the product sense round (14) and the behavioral / leadership round (5).

235 interview notes · updated Sep 2026

Pinterest·Software Engineer·Technical Phone Screen

Jun 2026
Pinterest coding screen for a software engineer role. One question, but it had enough edge cases to keep me busy for the whole session.
  • You have a class with a next() method that returns chunks of a string one at a time. The chunks may contain a two-character newline delimiter that can be split across consecutive chunks. Write a function that reads until the stream is exhausted and reconstructs the original lines correctly.

“The split-delimiter case is what got me at first.”

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Pinterest·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Pinterest ML engineer interview with a classic scale question that sounds straightforward but has a few layers worth thinking through.
  • Given a dataset with a million data points, would you choose a deep neural network or a KNN classifier, and why?

“KNN at a million points is basically a no-go unless you have serious infrastructure for it.”

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Pinterest·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed for an ML engineer role at Pinterest and got asked about regularization. Short and focused, nothing too wild.
  • Can you explain what regularization is and how it works?

“Bread and butter ML question but I still fumbled the explanation a bit.”

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Pinterest·Software Engineer·Technical Phone Screen

Jun 2026
Pinterest SWE interview with a string manipulation problem that looks trivial but has a few wrinkles worth thinking through.
  • Given two strings, return true if every character in the second string also appears somewhere in the first string.

“Used a hash set for the first string, then just checked membership while scanning the second.”

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Pinterest·Software Engineer·Technical Phone Screen

Jun 2026
Pinterest SWE interview with a string manipulation problem that had a sneaky follow-up. The core question was straightforward enough but the second part tripped me up a bit.
  • Given a numeric string, implement rounding to the nearest integer. For example, '3.5' should return '4' and '100.01' should return '100'. Follow-up: extend this to round to the last significant digit, so 124900 becomes 125000 and 12.49 becomes 12.5.

“The base case wasn't bad.”

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Pinterest·Data Scientist·Technical Phone Screen

Jun 2026
Pinterest Data Scientist interview with a coding-heavy problem around autocomplete. The question was more systems-flavored than I expected for a DS role, which threw me a bit.
  • Design an auto-complete system that takes (string, score) pairs as input and returns top dish suggestions for a given prefix, with support for real-time updates.

“I knew trie-based autocomplete at a surface level but hadn't thought through the scoring part carefully.”

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Pinterest·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Pinterest MLE interview that was basically one big deep-dive into your past work. They really want to see how you think about your own projects, not just what you built.
  • Walk me through your resume, pick the project you're most proud of, and do a deep-dive: what was the problem, what did you specifically contribute versus the rest of the team, what were the key technical decisions and trade-offs, what worked, what didn't, and what would you do differently now?

“This is the kind of question that sounds easy until you're actually in it and realize you've been giving credit to 'the team' for ten minutes without saying what you personally did.”

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Pinterest·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Pinterest system design round focused entirely on building a notification system from scratch. Pretty dense question with a lot of moving parts, and I felt like I was playing catch-up the whole time trying to cover everything they wanted.
  • Design an in-app notification system that handles real-time and persistent notifications (mentions, replies, system events), supports read/unread state, badges, and notification history, with requirements around low-latency fan-out, durability, idempotency, deduplication, and graceful degradation.

“I started with the data model which felt like the right call but I spent way too long there.”

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Pinterest·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Pinterest ML engineer interview with a meaty bagging/ensemble coding question that also required me to talk through theory. Not a leetcode grind session, more of a 'show me you actually understand the algorithm' kind of thing.
  • Implement bootstrap aggregation (bagging) from scratch in Python without NumPy, given an existing DecisionTree with fit and predict methods. Then discuss bias-variance trade-offs, the effect of the number of bootstrap rounds B, and out-of-bag estimation.

“The coding part was fine once I remembered to use random.choices for sampling with replacement.”

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Pinterest·Software Engineer·Technical Phone Screen

Jun 2026
Pinterest coding round with a graph/finance problem that looked straightforward but had a lot of depth once they started asking follow-ups about scale and overflow. Solid problem, decent experience overall.
  • You're given a list of debts between people as (debtor, creditor, amount) triples. Return the minimum number of transfer transactions needed to fully settle all balances. Any valid optimal solution is fine.

“I jumped straight to simulating the original edges and got tangled up.”

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