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Google interview notes, page 87 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
Went into a Google software engineering interview pretty underprepared on the coding side and paid for it. Got hit with a tree problem and it did not go well.
  • Given a root of a binary search tree and a key, delete the node with that key and return the updated tree's root.

“Did not practice trees nearly enough before this.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM interview at Google with a classic build vs. buy question. Nothing tricky on the surface but the depth they expected was real.
  • Your team needs a new system. Walk through how you'd decide whether to build it internally or purchase an existing solution, covering factors like cost, time-to-market, scalability, maintenance burden, vendor lock-in, and strategic differentiation.

“I started with cost and time-to-market because those felt safest, but I could tell partway through that wasn't landing as the interesting part.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, one algorithmic problem about sorting an almost-sorted array. Pretty focused session, no fluff.
  • Given an array where each element is at most K positions away from its sorted position, sort the array efficiently.

“My first instinct was to just throw a standard sort at it and call it a day, but that felt too easy for Google.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview, one question about building a product around a hypothetical teleportation device. Pretty open-ended and a bit disorienting if you're not used to pure ideation prompts with zero constraints.
  • If you had access to a teleportation device, how would you go about building a product around it?

“I went straight to consumer use cases and kind of rambled for a minute before realizing I hadn't defined who the user was or what problem teleportation actually solves for them.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a single market sizing question about in-flight advertising. Pretty lean on details but the question itself is a decent one to prep for if you're going into any ads-adjacent role.
  • Estimate the total market size for in-flight advertising.

“My first instinct was to go top-down: start with global air passengers per year and work toward ad impressions and revenue.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google data science interview with a communication-focused question that sounds easy until you're actually in the room trying to explain it without sounding condescending.
  • How would you explain precision and recall to a non-technical stakeholder?

“I thought I had this cold.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE onsite coding round with two algorithmic problems. Nothing too wild but the DP one had a nice optimization angle that I didn't fully see coming.
  • A 2D dynamic programming problem that can be reduced to a 1D DP solution for better space efficiency.
  • A graph connectivity or grouping problem solvable with either Union-Find or BFS/DFS.

“Started with the 2D table approach which felt natural and got it working, but then they asked if I could do better on space.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE coding round, one problem the whole time. Seemed straightforward on the surface but the edge cases around duplicate letters made it messier than expected.
  • Given a list of letters that may contain duplicates, count the number of distinct ways to select and arrange letters from that list to spell the word 'GOOGLE'.

“My first instinct was to just count frequencies and do some combinatorics math, but they pushed toward a backtracking solution.”

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Google·Software Engineer·Onsite - Product Sense / Strategy

May 2026
Interviewed for a PM role at Google and got hit with an estimation question about Gmail storage planning. Pretty classic product sense meets data reasoning combo, but the scale of Gmail makes it way less straightforward than it sounds.
  • You're the PM for Gmail. How would you figure out how much storage to purchase for the next year?

“I started with current user base and average storage per user, then tried to layer in growth projections and attachment trends.”

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Google·Machine Learning Engineer·Technical Phone Screen

May 2026
Google ML Engineer interview with a graph connectivity problem that looked deceptively simple on the surface. The follow-up about scaling was where things got interesting.
  • You have a set of 2D points, a start point, an end point, and a distance function getDistance(p, q). Two points are connected if their distance is below a threshold r. Determine whether a path exists from start to end.
  • If the point set is very large and getDistance is expensive to call, how would you minimize redundant distance computations and avoid checking every pair of points?

“My first instinct was BFS, which is fine, but I fumbled a bit explaining why I didn't need to build the full adjacency list upfront.”

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