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Meta interview notes, page 145 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·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Meta for a software engineering role. Pretty standard stuff, nothing that'll surprise you if you've done a few of these before.
  • Tell me about a time you received constructive feedback and how you responded to it.
  • Describe a situation where you had a conflict with a teammate or colleague and how you handled it.

“Went with a situation from a past project where my code review feedback was apparently too blunt.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round with a recursive problem that seems easy until you actually start implementing it.
  • Given a nested list of integers, compute a weighted sum where each integer is multiplied by its depth in the nesting. Depth starts at 1 for the outermost level.

“Spent the first couple minutes just re-reading the problem because I kept second-guessing what 'depth' meant.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta coding interview with a grid manipulation problem that looks straightforward until you actually sit down and think about the symmetry constraints. One question, medium-to-hard difficulty, left me second-guessing my approach the whole time.
  • Given an n x n grid (n is odd) where each cell holds a value of 0, 1, or 2, find the minimum number of cells you need to change so that the grid contains a valid 'Y' shape. The Y is defined by the two top diagonals meeting at the center plus a vertical line going down from the center, all sharing one value, with every other cell sharing a different single value.

“I spent way too long trying to brute force the value assignments before realizing you only have a small number of candidate (Y-value, background-value) pairs since both values are drawn from {0,1,2} and they have to be different.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta coding screen, got a data structures question that felt straightforward on the surface but had a few wrinkles worth thinking through.
  • Design a data structure to represent a sparse vector efficiently, then implement a dot product method that takes another sparse vector as input.

“My first instinct was to just use a plain array and I almost went with it before catching myself.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE interview where they handed me a broken maze solver and told me to fix it with AI tooling. Basically a debugging exercise on an unfamiliar codebase, grid-based maze with walls, a start, and an end point. Straightforward premise but the pressure of reading someone else's code fast is real.
  • You're given a buggy maze solver codebase. The maze is represented as a grid with walls, a start point S, and an end point E. Some tests are failing. Use an AI coding assistant to read the code, figure out what's broken, and fix it.

“The tricky part wasn't finding the bug, it was orienting myself in code I'd never seen before.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round with a graph/social problem that looks easy until you actually read the conditions carefully. Nothing too wild but the edge cases will bite you if you're not paying attention.
  • Given a list of user ages, count the total number of valid friend requests that can be sent across all users, based on a set of age-based eligibility rules.

“The conditions look straightforward but i kept second-guessing which rule took priority.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta DS interview with a SQL-heavy technical screen focused on feed analytics. Two questions, both involving joins across watch-time and reaction tables. Nothing too exotic but the window function logic tripped me up a bit.
  • Write a SQL query to count the number of posts that received more than 60 seconds of viewing time from unconnected viewers within the last 7 days.
  • Write a SQL query to compute the average number of reactions per post, broken out by whether the viewer is a friend or unconnected, over the last 7 days.

“Straightforward filter on the views table but I initially forgot to scope the date range properly.”

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Meta·Data Scientist·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Meta for a Data Scientist role, focused entirely on cross-functional work and how you handle the messier parts of the job like conflict, shifting priorities, and acting on feedback you didn't ask for.
  • Tell me about a time you drove impact that went beyond your immediate team. What was your role and what came of it?
  • Describe a time you received critical feedback and acted on it. What specifically changed about how you worked?
  • Walk me through a conflict you had at work and how you resolved it.
  • Tell me about a time you had to quickly reprioritize your roadmap. What trade-offs did you make and how did you decide?

“I had a decent story here but I think I spent too long on the setup and rushed the actual outcome.”

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Meta·Product Designer·Onsite - Product Sense / Strategy

Jun 2026
Meta product design interview, one question and a sketching component. Pretty open-ended, which I wasn't fully prepared for.
  • Design a Facebook-like social platform specifically for doctors. Include a rough UI sketch.

“The sketching part threw me more than the actual product thinking.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Meta for a software engineer role, basically a full eBay clone from scratch. A lot of ground to cover and the interviewer kept pushing on the hard parts like bid concurrency and auction lifecycle management.
  • Design a large-scale online auction marketplace similar to eBay, supporting fixed-price and auction listings, bidding, automatic auction ending, payments, shipping tracking, and ratings.
  • How would you model the core data entities for this system: users, listings, bids, and transactions?
  • How do you handle bid concurrency to ensure correctness when multiple users are bidding simultaneously on the same auction?
  • Walk through the auction lifecycle service: how does an auction end automatically and how is the winner determined?
  • How would you design the search and indexing layer to support low-latency browsing and filtering of millions of active listings?
  • How would you integrate payments and handle anti-fraud detection in this marketplace?
  • How would you design the notification system to alert users about outbid events, auction endings, and shipping updates?

“This is a beast of a question.”

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