← Back to Directory

Google interview notes, page 119 of 215

FAANG / Big Tech

Most of these Google write-ups come from Software Engineers (1,167), then Product Managers (686) and Data Scientists (125). The most reported rounds are the product sense round (667), the technical phone screen (660), the behavioral / leadership round (252) and the onsite coding round (214).

2146 interview notes · updated Oct 2026

Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE coding round, one main problem with a follow-up bolted on. The base problem was a known LeetCode variant dressed up in chess clothing, which I appreciated more than a straight 'here's the problem number' situation. The follow-up with walls was where things got genuinely interesting.
  • Given two strings of equal length over the characters R, L, and underscore, where R can only slide right into empty squares and L can only slide left into empty squares, determine whether some sequence of moves can transform the first string into the second.
  • Extend your solution to handle a new immovable wall character. Walls cannot be crossed by any piece, never move themselves, and must appear at identical positions in both strings. The reachability check now applies independently within each segment between walls.

“The chess framing threw me for about thirty seconds before I realized what was actually being asked.”

View Post

Google·Machine Learning Engineer·Technical Phone Screen

May 2026
Google ML Engineer interview with a tricky DP problem involving ad selection under a sliding window revenue constraint. Two variants made it more interesting than a typical knapsack rehash.
  • Given a sequence of ads each with an associated revenue, select a subset of ads to maximize total revenue such that the sum of revenues in any consecutive T time units stays below a threshold M. Solve both the case where each ad can be selected at most once, and the case where ads can be reused.

“The two-variant structure is what got me.”

View Post

Google·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Google for a software engineer role. Just one question but it took up the whole session, which I wasn't expecting.
  • Tell me about your greatest achievement outside of work. Walk through the situation, what you were trying to accomplish, what you actually did, and what came of it. Then connect it to something relevant to this role.

“I picked a marathon I trained for solo over six months, which felt concrete enough.”

View Post

Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview, product strategy round. Just one question but it's the kind that can swallow you whole if you're not careful about scope.
  • Define a 10-year product roadmap for Google Maps.

“The time horizon is what gets you.”

View Post

Google·Data Scientist·Technical Phone Screen

May 2026
Brutal technical screen for a DS role at Google. The whole thing was essentially one giant question about a model you know well, but the sub-parts went deep enough that it felt like six separate interviews compressed into one.
  • Pick a predictive model you know well and explain how it works end-to-end for a real problem you've solved, including the objective, loss function, and the assumptions the model makes. When do those assumptions break down?
  • How did you handle feature engineering and validation strategy for that model? Specifically, how did you prevent data leakage and verify that your feature distributions were stable over time?
  • Walk me through the actual training process: hyperparameter search, regularization, early stopping, and how you dealt with class imbalance. Can you justify those choices with numbers?
  • Describe three specific problems you ran into during training or inference, like covariate shift, label noise, or latency issues. How did you detect and fix each one?
  • How do you evaluate a model beyond standard ROC or PR curves? Talk about calibration, cost-sensitive metrics, and how you connect model performance to actual business value.
  • How do you think about fairness and privacy for this kind of model, and what does your post-deployment monitoring setup look like? What triggers a rollback?

“I picked gradient-boosted trees and talked through a churn prediction problem.”

View Post

Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, second in the loop. Got a variant of a classic graph/dynamic programming problem and it went well, probably the cleanest round I've had in a while.
  • Given a grid with bombs placed at various cells, find the maximum number of bombs you can detonate if each bomb triggers others within its blast radius (a variation on the classic chain detonation problem).

“Had seen this one before, so the solution came fast.”

View Post

Google·Technical Program Manager·Onsite - Multi Round

May 2026
Went through a TPM loop at Google and got hit with a metrics question that sounds straightforward until you actually have to answer it out loud.
  • How do you develop metrics for a project?

“I fumbled the opening by jumping straight into output metrics without grounding it in goals first.”

View Post

Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview, one question about improving internet access across Africa. Short session, felt more like a product strategy case than a standard product sense question.
  • How would you improve internet coverage in Africa?

“I went straight to infrastructure and blanked on the demand side for a solid minute.”

View Post

Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, classic interval scheduling problem with a distributed systems twist at the end. The follow-up about handling massive input was where things got interesting.
  • Given a list of meeting time intervals, find the minimum number of conference rooms needed so no two overlapping meetings share a room.

“Got through the core solution fine.”

View Post

Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Fourth and final round of a Google SWE loop, purely algorithmic. The problem was graph-based and deceptively short to describe but easy to get subtly wrong in implementation.
  • Given a directed graph and a specific node v, find the length of the shortest cycle that passes through v. Return -1 if no such cycle exists.

“The bug I almost shipped: I marked v as visited right at the start of BFS, which completely blocks it from ever being rediscovered.”

View Post