← Back to Directory

Google interview notes, page 184 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·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Interviewed at Google, got a product estimation question about the Play Store. Pretty standard PM case but the numbers got messy fast.
  • Estimate how much revenue the Google Play Store generates annually.

“I started with the 30% cut Google takes and tried to build up from DAU estimates for Android users.”

View Post

Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a single estimation question about street view data loss in New York. Pretty classic market sizing territory but the geographic constraint made it a bit more interesting than the usual 'how many gas stations' type prompt.
  • Estimate the cost to replace lost street view imagery data for Google Maps in New York.

“My first instinct was to jump straight to car fleet costs and I almost forgot about the data processing side entirely.”

View Post

Google·Software Engineer·Technical Phone Screen

Jun 2026
Conceptual ML foundations interview for a Research Scientist role at Google. No math derivations, just explanations of core ideas, but don't let that fool you into underpreparing. The breadth caught me a little off guard.
  • What is the difference between overfitting and underfitting, and how do you identify each?
  • Can you explain Bayesian inference and the concept of likelihood?
  • What is perplexity and what does it measure in the context of language models?
  • Why do Transformers generally outperform RNNs, particularly for long sequences?
  • What is the computational complexity of matrix multiplication, and how does it relate to autoregressive decoding in Transformers?
  • What are the differences between SGD, Adam, and AdamW as optimizers?

“Felt solid here.”

View Post

Google·Software Engineer·Hiring Manager Screen

Jun 2026
Quick and slightly disorienting team match call for a software engineering role at Google in Bangalore. The interviewer jumped straight in, challenged a database sharding answer, and wrapped up in about 20 minutes flat. Left me with more questions than answers.
  • Walk me through your past experience, with a focus on anything related to scalability.
  • Several object-oriented programming concept questions.

“I brought up database sharding and he pushed back immediately, said something was wrong with how I described it.”

View Post

Google·Software Engineer·Hiring Manager Screen

Jun 2026
Interviewed for a business analyst role at Google. Just the one question from what I can tell, focused on product metrics. Nothing too wild but it made me think harder than I expected.
  • How would you determine whether a new feature launch was successful?

“I went straight to engagement metrics and kind of stalled when they pushed back asking what 'successful' even means.”

View Post

Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Got a classic estimation question at Google, the kind where you realize halfway through that your first assumption was completely wrong and you just have to keep going.
  • If the entire U.S. population switched to self-driving cars, how many vehicles would be needed to meet demand?

“Started by anchoring on total U.S.”

View Post

Google·Machine Learning Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Google for an ML engineer role. One big open-ended question about building an experiment tracking platform, which sounds straightforward until you realize how many directions it can go.
  • Design an ML experiment tracking and analysis platform.

“I started with the basics: logging runs, storing hyperparameters, tracking metrics over time.”

View Post

Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, one question on recipe dependencies. Pretty clean problem once you see the graph structure, but I fumbled around for a bit before getting there.
  • Given n recipes, each with a list of required ingredients and an output, plus a list of initially available supplies, return all recipes you can actually make. A recipe can be made if every ingredient is either in your supplies or is itself a makeable recipe.

“Took me longer than it should have to see this as a graph problem.”

View Post

Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview with a tree design problem that started simple and got complicated fast. The follow-ups kept stacking and I wasn't fully prepared for how deep they'd go on deletion edge cases.
  • Design an employee hierarchy class that supports adding an employee under a given manager and deleting an employee by ID. How do you handle deleting a manager, deleting the root/CEO, and preventing cycles in the hierarchy?
  • Follow-up: each employee has a seniority level. When deleting a manager, how do you pick which employee in that manager's subtree gets promoted as the replacement? What if there's a tie in seniority?

“I started with a basic map from id to node and got addEmployee working pretty quickly.”

View Post

Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a stats-heavy experimentation question. Not much context about the full loop but this one question stuck with me.
  • You need to run an A/B test but you're short on time or don't have enough users to reach statistical significance. What do you do?

“I went straight to 'increase traffic allocation' and 'shorten the test window' and the interviewer kind of waited like they expected more.”

View Post