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Meta interview notes, page 111 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·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
ML system design round at Meta, two big topics back to back: recommendation systems and notification ranking. Discussion-style, so less 'here's my answer' and more going back and forth with the interviewer. Felt like the kind of session where knowing the vocabulary matters as much as knowing the concepts.
  • Design a short-video recommendation system (think TikTok or Instagram Reels style). Walk through your architecture end to end.
  • How would you design a nearby-place recommendation feature? What changes compared to a standard content recommendation system?
  • Given a mix of notification types (likes, comments, friend activity, ads, system messages), how would you rank and decide which notifications to send to a user and when?

“This is the bread and butter of ML design rounds at big social platforms, so I wasn't surprised.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a single product design question focused on fashion. Pretty open-ended and I kept second-guessing whether they wanted me to go broad or pick a lane early.
  • How would you design a fashion product for Facebook?

“I spent the first minute or two just trying to figure out what angle to take.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round, one problem but they really dug into it. Not just 'does your code work' but 'explain every tradeoff you made and why.' Felt more like a design conversation than a pure leetcode session.
  • Given an integer array and an integer k, count the number of contiguous subarrays whose elements sum to k. You need a solution better than O(n²), and you have to explain your time and space complexity, how you handle negative numbers and zeros, and any integer overflow concerns.

“The subarray sum part I knew, prefix sums with a hashmap, seen it before.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview with a SQL-heavy technical screen. Two questions, both involving the same schema, and the second one had enough moving parts that I had to slow down and think out loud more than I wanted to.
  • Given a schema with users, sessions, calls, and call_participants tables, write a query to return the distinct users who initiated at least one call (group or 1:1) within a specific 7-day window.
  • Using the same schema, compute the percentage of French daily active users who participated in at least one call on a specific date. Output the reference date, total French DAUs, the count who were on a call, and the percentage rounded to two decimals. Write it as a single SQL script using CTEs.

“Pretty straightforward join between calls and a date filter.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta data scientist interview with a probability question about sampling. Pretty math-heavy, no fluff, just straight into the problem.
  • You have 1,000 people and each day you draw 10 names. If you sample without replacement (no one gets picked twice until everyone has been chosen), what day do you expect a specific person to be first selected? Then redo the problem assuming sampling with replacement.

“The without-replacement case clicked pretty fast once I thought about it as a uniform distribution over 100 days.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM interview at Meta with a product sense question about cross-platform user behavior. Pretty classic Meta territory but still tricky to nail without a clear framework in your head.
  • How would you persuade users who only use Facebook to start using Instagram as well?

“I fumbled the opening a bit by jumping straight into feature ideas before thinking about why someone would resist switching in the first place.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta data scientist interview with a product-heavy case on ad monetization. The whole thing was basically one big scenario question about where to draw the line on ad frequency before you start burning users.
  • How would you find the optimal ad load for users, accounting for diminishing revenue returns and the risk of losing users over time?

“This is one of those questions that sounds like a metrics question but is really a strategy question wearing a metrics costume.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round, pretty much what you'd expect. One algorithm question, stack-based, nothing too wild but you still have to actually think it through.
  • Given a string containing only bracket characters, write a function to determine whether the brackets are all properly opened and closed in the correct order.

“Classic stack problem.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

May 2026
Meta SWE coding round, and they threw a pretty gnarly in-memory database design question at me. Lots of moving parts: TTL, conditional writes, historical reads. More of a mini system design disguised as a coding problem than a pure algo question.
  • Design and implement an in-memory key-value store (keyed by a composite key of `key` and `field`) that supports TTL-based expiration, conditional update and delete operations, prefix-based field scanning, and historical value lookups at arbitrary past timestamps.

“This one took me a minute to even parse.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding screen, one question on range sum queries. Pretty straightforward if you've seen prefix sums before, but I fumbled explaining the tradeoff between preprocessing and query time more than I'd like to admit.
  • Given an integer array and repeated range sum queries, design a class that preprocesses the array so each query runs in constant time.

“I knew prefix sums going in, so the implementation wasn't the issue.”

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