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Meta interview notes, page 125 of 238

FAANG / Big Tech

Most of these Meta write-ups come from Software Engineers (1,194), then Data Scientists (489) and Product Managers (453). The most reported rounds are the technical phone screen (1,190), the product sense round (466), the system design round (255) and the behavioral / leadership round (205).

2377 interview notes · updated Jul 2026

Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a single product design question about building a borrowing and lending feature on Facebook. Pretty open-ended, which I wasn't fully prepared for.
  • How would you design a borrowing and lending solution for Facebook?

“I went straight to the marketplace angle because Facebook already has that surface, but in hindsight I think they wanted me to slow down and really question who the user is first.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round with a string parsing problem. Not the hardest thing I've ever seen but there are enough edge cases to trip you up if you're not careful.
  • Given two strings, implement a function that checks whether the first string is a valid abbreviation of the second. An abbreviation is formed by replacing any non-empty substring with the numeric length of that substring (e.g. 'i18n' matches 'internationalization' but not 'interpolation').

“My first instinct was to use regex and I immediately talked myself out of it, which was probably the right call.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta coding interview with one algorithmic question and a follow-up optimization angle. Pretty focused session, nothing behavioral.
  • Given N integer intervals [a, b] where all endpoints are positive integers, find an integer that is covered by the most intervals. Any valid answer works if there's a tie. Follow-up: if all endpoints are bounded by some small value M, how would you change your approach?

“The base problem I got through fine.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta data scientist interview where a stakeholder scenario was used to probe statistical fundamentals. The question was framed as a live experiment review which added some pressure I wasn't expecting.
  • Define p-value, statistical power, Type I error, and Type II error in the context of A/B testing. Then explain why testing multiple metrics or variants requires corrections like Bonferroni, and walk through a concrete example.

“The definitions part was fine, I've explained these enough times that it's almost muscle memory.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round, one tree problem the whole time. Pretty focused session, nothing too wild but the follow-up pressure was real.
  • Given a binary tree where each node holds a single digit (0-9), every root-to-leaf path spells out a number. Write a function that returns the sum of all those numbers.

“I went with DFS and accumulated the current number by multiplying by 10 and adding the node value as I went down.”

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Meta·Software Engineer·Onsite - System Design / Architecture

May 2026
Meta system design round, got asked to design Reddit. Pretty open-ended, which I wasn't fully prepared for.
  • Design Reddit. Walk through the architecture for a large-scale social news and discussion platform.

“Spent the first few minutes just trying to nail down scope because Reddit does a lot of things.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview with a meaty product sizing and experimentation question. The kind of prompt that sounds like one question but is actually five questions stacked in a trench coat.
  • Before committing engineering resources, how would you assess whether a new e-commerce product line is worth running an experiment on? Walk through your sizing approach from both a top-down and bottom-up perspective, and estimate what share of users would actually be affected.
  • How do you calculate the minimum detectable uplift that would make a test economically worthwhile, factoring in fixed costs and the opportunity cost of routing traffic to the experiment?
  • Lay out a concrete test plan for this new product line, including targeting, rollout ramp, primary KPIs, counter-metrics, and the go/no-go decision criteria.
  • How would you detect and de-risk cannibalization of existing product categories, and what leading indicators would you track before revenue numbers become meaningful?
  • If short-term engagement metrics drop during the experiment but you believe long-term retention will improve, what do you do?

“This is where I spent most of my time and probably got too deep too fast.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

May 2026
Meta SWE coding round focused on tree problems, specifically the diameter/longest path family. The interviewer pushed through multiple variants of the same core DFS idea, which I wasn't fully expecting.
  • Find the diameter of a binary tree, i.e. the longest path (in edges) between any two nodes.
  • Extend the binary tree diameter solution to a general N-ary tree where each node can have any number of children.
  • What if instead of longest path by edge count, you needed the longest strictly monotonic path in a BST, where node values must be sorted along the path?

“The classic mistake I almost made: I started writing the DFS to return the diameter directly.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview with a product metrics question centered on a B2C chat app. Pretty standard setup but the question had enough layers to trip you up if you went shallow.
  • How would you measure the overall success of a B2C chat application? Walk through both core and secondary metrics you'd track.

“I started with engagement stuff like response time and conversation completion rate, which felt right, then got a bit lost trying to decide where retention fits versus revenue.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta coding interview with a classic matrix traversal problem. Not much context given but the problem itself is a solid one if you've done any backtracking prep.
  • Given a 2D grid of characters, write a function that finds all valid words that can be formed by traversing adjacent cells.

“Classic backtracking problem and I'd seen it before, but I still fumbled the visited-cell tracking on my first pass.”

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