Google Interview Questions

Reconstructed from 111 verified candidate reports across 48 questions. Apr 2026 – Oct 2026 (DeepMind from Aug 2025).

How the Googleinterview runs, round by round, and how to prepare for it — built from candidate reports, not from job descriptions or one founder’s memory. The catalog gets a refresh pass every month.

AceOffer is not affiliated with, endorsed by, or sponsored by Google. Questions are reconstructed from interview experiences candidates shared, not from Google materials.

111
candidate reports
48
distinct questions
7
round types
Monthly
refresh cadence

Key facts

  • •48 distinct Google interview questions indexed
  • •111 candidate reports across the catalog
  • •Round mix across candidate reports: behavioral 43%, coding 37%, ML / research 7%, online assessment 6%
  • •33 of the 48 questions were last reported in Aug–Oct 2026
  • •Reports span Apr 2026 – Oct 2026 (DeepMind from Aug 2025)
  • •Refreshed monthly · last updated October 2026

Browse Google interviews by topic

The Google loop, from candidate reports

Reported Google software engineering loops start with the Google Hiring Assessment, a work-style questionnaire with no coding, and some new grad and early career candidates also take a two-problem coding assessment on HackerRank. Round 1 is usually two back-to-back video interviews, one coding and one Googleyness and leadership. The onsite is usually two coding interviews for L3 and L4, held in person in most 2026 reports; L5 and above add system design, and from September 2026 some L4 loops add a Solution Design round. Coding is LeetCode-style with Google settings and follow-ups: the earliest time everyone in a friend log is connected and what changes when people unfriend, Number of Islands and its variants, Meeting Rooms variants, course schedule variants, and the fewest cars for a set of rental reservations. Machine learning loops add an ML domain interview, on topics from LLMs and Transformers to your own projects, and an ML design such as a recommendation system. Google DeepMind runs its own loops, with research conversations or a research presentation, ML foundations questions and, in most reported loops, coding rounds.

What does Google ask in each interview round?

Google interviews span 7 distinct round types, broken down below. Counts reflect distinct questions per round, not number of times asked.

LeetCode-style problems with follow-ups: the earliest time everyone is connected (LeetCode 1101) then unfriend, Number of Islands variants, Meeting Rooms variants, course schedule variants, car rental fleet size, and the longest non-decreasing subarray if one element may change.
24 questions

The Googleyness and leadership interview: conflict, a project you are proud of, mistakes and feedback, prioritisation, ambiguity and working across teams.
11 questions

ML domain interviews on LLMs, Transformers and post-training, and ML designs such as YouTube Watch Next or predicting a molecule pair's reaction factor.
3 questions

The Google Hiring Assessment (most-like and least-like-me choices, agreement scales and workplace scenarios) and, for some early career candidates, a two-problem HackerRank assessment: fixing a feature-rollout codebase with a built-in AI assistant and an email verification checksum.
3 questions

A recommendation system, a rate limiter for AI output tokens, a web crawler and, on DeepMind's Android team, the Gemini app.
3 questions

The Round 1 coding interview, usually one problem with follow-ups, such as the total size of a file or directory and then validating the file system, or counting clusters of 2D points within a radius.
2 questions

DeepMind research deep dives on your own work and its assumptions, and quick-fire questions such as multiplying matrices split across two GPUs.
2 questions

The Google question list

48 questions, grouped by round, with how often candidates reported each one and when it was last seen. Create a free account to see the list and open the free preview questions.

Browse the Google questions →
What passing candidates do
  • •Preparing the follow-up, not just the base problem. The friend-log question moves on to unfriend events, Number of Islands to adding land and inland lakes, and Meeting Rooms to free slots and on-duty segments; one candidate says finishing the main problem is only the pass line.
  • •Having several specific stories for the Googleyness interview. Reports list disagreement, a project you are proud of, a mistake, and too much work, with follow-ups that ask for more detail and what you would do differently.
  • •Agreeing on the approach and edge cases before coding, then dry running your own tests out loud. Code is written in a document or plain editor without running it, and several candidates name clarifying and talking through their thinking as what interviewers look for.
Where candidates lose points
  • •Coding before aligning with the interviewer. One rejected candidate's feedback named missed corner cases and communication, and one L4 candidate who solved both onsite problems was rejected for a lack of communication.
  • •Skipping the brute force when it is wanted. In both 2D clustering reports, the interviewer preferred or asked for the brute-force version after the candidate discussed faster neighbour searches.
  • •Answering the Hiring Assessment's repeated work-style questions inconsistently. Five candidates advise picking a consistent work style, since the same traits come back in different wording.
  • •Preparing DeepMind research rounds from research alone. Reports describe ML foundations questions, from overfitting to Transformer internals and normalisation, alongside the research discussion.

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Send them this guide: 48 questions from 111 candidate reports, with the rounds, the follow-ups and what passers do.

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