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Meta interview notes, page 94 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
PM interview at Meta, one question about measuring success for AI messaging features. Not much else to go on but it's a meaty enough topic that I spent a while unpacking it.
  • How would you define and measure success for Meta's AI-powered messaging features?

“This took me a second to scope properly.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round with a graph/shortest-path problem. Pretty standard setup but the round-trip twist made it less obvious than it first looked.
  • Given a list of flights with source, destination, and price, find the minimum cost of a round-trip starting and ending at city A.

“My first instinct was just Dijkstra from A and call it a day.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

May 2026
Meta SWE coding round with a library simulation problem. Nothing too wild on the surface but the edge cases around price ordering and reclassification tripped me up more than I expected.
  • Design a library book circulation tracker that processes acquisition, checkout, and reclassify operations on a collection of books, where each book has a category and an insurance value. Checkouts should always remove the least valuable books first. Return the total insurance value for each checkout operation across the full sequence.

“I started with a plain dict mapping category to a list of prices and sorted on checkout.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview, product sense round. One question but it had some teeth to it. Left feeling like I could've pushed harder on the prioritization piece.
  • Pick a popular product you use regularly. How would you design a direct competitor, and which features would you prioritize building first?

“I picked a product I actually use every day thinking that'd make it easier, and it sort of backfired because I spent too long in the 'I love this product' phase instead of getting to the competitive angle.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a classic product design question. One question, open-ended, and the kind that sounds easy until you're actually sitting there trying to say something that doesn't sound generic.
  • You're a PM at Meta. Design a product for volunteering. What would you build and why?

“I spent the first minute trying to figure out why Meta would even care about volunteering, which was actually the right instinct but I didn't lean into it enough.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta product sense round, one open-ended design question about building something to help people get a pet. Not a lot of context to work with, which was kind of the point.
  • Design a product that helps someone find and adopt a pet.

“I went straight to the adoption flow and probably spent too long on search filters before they nudged me toward the actual user problem.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta software engineering interview with a design-heavy coding question around a payment ranking system. The question had multiple layers and required thinking through data structures out loud, which I was not fully prepared for.
  • Implement a function topNPayers(n) that returns the n accounts with the highest total outgoing payment amounts, formatted as 'accountId:totalOutgoing'. The system should support live updates as new debits come in. Walk through your choice of data structure, how you handle ties, and the time and space complexity for both updates and queries.

“The core logic clicked pretty fast but I fumbled explaining the tie-breaking rules.”

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

May 2026
System design round at Meta for an MLE role. The prompt was a full-blown photo and video storage platform at global scale, covering basically everything from upload mechanics to disaster recovery. Brutally broad.
  • Design a system to store and deliver user-generated photos and short videos at global scale, covering upload, download, deletion, listing, thumbnail and transcode generation, search by owner or metadata, signed access URLs, and per-user quotas.

“The scope of this thing is genuinely wild.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview with a meaty SQL prompt centered on a dating app funnel. One question, but it had a lot of moving parts and I probably underestimated how long it would take to think through cleanly.
  • You work on a dating app. Write a SQL report covering 2025-08-25 through 2025-09-01, with one row per day, gender, and age bucket (18-24, 25-34, 35-44, 45+). For each group compute: profile creation count, photo present rate, average completion rate (filled fields divided by total fields), distinct profile viewers, likes sent, and match rate (matches divided by views). Also return a separate result set of user IDs whose profiles are missing a photo as of 2025-09-01. Ages should be computed from birthdate at the report date. Return two result sets.

“The age bucketing tripped me up first.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta data scientist interview with a probability question that sounds deceptively simple until you actually try to set up the math under pressure.
  • 95% of accounts are real and 5% are fake. Fake accounts send friend requests at 10 times the rate of real accounts. If you receive a friend request, what is the probability it came from a fake account?

“I knew it was a Bayes problem the second I heard it but still fumbled the setup.”

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