Google Interview Questions — Page 197

Google·Software Engineer·Onsite - Multi Round

Jul 2026

Onsite loop at Google for a software engineer role, multiple coding rounds plus system design. The coding portions were rough in spots but system design felt solid, and now it's just a waiting game to see if the stumbles were bad enough to matter.

Implement an algorithm that returns a single set of unique results (rather than multiple sets), and analyze its time complexity.
Re-implement the previous problem using an alternative approach, write pseudo-code for a third approach, and discuss the amortized complexity of the solution.
Design a system for a large-scale product (system design round).
Behavioral and culture-fit questions covering past experience and working style.

“Needed a second example from the interviewer before the problem clicked, which ate up like 15 minutes.”

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Google·Software Engineer·Technical Phone Screen

Jul 2026

Phone screen for a software engineering intern role at Google with two back-to-back coding problems. Pretty standard algo stuff but the second question tripped me up more than I expected.

Given an m x n grid where '1' represents land and '0' represents water, count the number of islands. Islands are formed by horizontally or vertically connected land cells, and the grid edges are all surrounded by water.
Given an array of uppercase letters, count the number of ways to select letters from the array such that the selected letters can be rearranged to spell GOOGLE. Each index is treated as a distinct choice even if two indices hold the same character.

“Classic BFS/DFS problem and I knew it the second I read it.”

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Google·Software Engineer·Onsite - System Design / Architecture

Jul 2026

Google system design round for a software engineer role. The whole question was basically one giant prompt about building an AI-powered anomaly detection service for OS snapshots, with a lot of moving pieces to cover in not enough time.

Design an AI-based anomaly detection service that ingests OS snapshots, classifies machines as normal or abnormal, triggers automated actions like shutdown or quarantine, sends warning emails, and lets clients query warning history. Cover data collection, model serving, decisioning, action orchestration, audit storage, access controls, and failure rollback.

“This is a beast of a question.”

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Google·Software Engineer·Technical Phone Screen

Jul 2026

Google coding interview with a single IP address validation problem. Pretty standard technical screen, nothing too wild, but the edge cases will get you if you're not careful.

Write a function to validate whether a given string is a valid IPv4 or IPv6 address.

“The core logic isn't hard but I kept second-guessing myself on the edge cases.”

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Google·Software Engineer·Recruiter / HR Screen

Jul 2026

Early stages of a Google Software Engineer interview process, based in Madrid. After applying, a recruiter reached out quickly and set up a chat, which led to a first round covering algorithms and a leadership section. The candidate is still mid-process and curious about logistics for the onsite, specifically whether Google covers travel and accommodation.

Does Google arrange and cover flights and hotel for candidates who need to travel for an onsite interview?

“Not really an interview question but something I genuinely couldn't find a clear answer to.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jul 2026

Google SWE coding round, one problem the whole time. The question was LeetCode 2402 and they wanted more than just the heap solution.

You have n meeting rooms numbered 0 to n-1 and a list of meetings as half-open intervals. Rooms are assigned by specific rules around delays, smallest available room index, and reuse priority. Return the room that held the most meetings, breaking ties by smaller index.

“Got the two-heap approach out pretty quickly, free rooms as a min-heap on index, occupied rooms as a min-heap on (end_time, room_index).”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jul 2026

Google PM interview with a single product design question. Pretty open-ended and a bit disorienting if you're not used to hardware-adjacent prompts.

Design a smart hat.

“My first instinct was to laugh, which I managed to suppress.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jul 2026

Google product case question about estimating incremental revenue from expanding a food delivery app into a new vertical. Pretty lean on context but the core of the question is a market sizing and monetization exercise.

How would you estimate the incremental revenue a food delivery company could generate by expanding into a new vertical?

“I went straight into sizing the addressable market for the new vertical and tried to break down revenue by attach rate and average order value.”

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Google·Software Engineer·Technical Phone Screen

Jul 2026

Google SWE interview with a pretty gnarly string/parentheses problem that had me second-guessing my approach the whole time. The problem felt deceptively clean on the surface but the deletion constraint interaction made it genuinely hard to reason about.

You're given a string of parentheses and digits. Each digit v at position i requires you to delete exactly v parentheses that appear before it in the string, with no parenthesis deleted more than once across all digits. Digits are ignored when checking validity. Does there exist a valid set of deletions such that the remaining parentheses form a valid sequence? Describe an efficient algorithm, its complexity, and optionally produce a witness deletion set.

“I stared at this for a solid minute before saying anything.”

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Google·Data Scientist·Technical Phone Screen

Jul 2026

Stats-heavy technical screen for a DS role at Google. The whole thing was basically applied inference from start to finish, no product sense, no SQL, just probability and estimation. Walked out feeling okay about the first half and less okay about the truncated normal stuff at the end.

You collected a sample and want to test whether the population mean differs from 0. What does a p-value of x% mean in this context?
Given a sample mean of 1 and a standard error of 0.1, construct a 95% confidence interval for the population mean.
What sample size would you need to reduce the standard error from 0.1 to 0.01, and what can you do if you can't increase sample size?
Given independent observations from some distribution, propose an estimator for the probability that X exceeds 10, then construct a 95% confidence interval for that probability and interpret the resulting interval.
You have 1,000 binary features and want to estimate an overall conversion rate. How would you design the estimation or sampling strategy?
Assume X follows a normal distribution but you only observe values where X exceeds a threshold of 3 (truncated normal). How would you estimate the mean and variance, and how would you construct confidence intervals for them?

“Knew this cold but still second-guessed my wording mid-answer.”

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