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Meta interview notes, page 65 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 focused on product reasoning and metrics for an internal video-chat tool. Pretty open-ended, which I wasn't fully prepared for.
  • You're a PM at Meta. Why did Meta build Rooms, its internal video-chat product competing with Zoom? How would you define goals and measure success for it?

“Two questions crammed into one, which I didn't fully appreciate until I was halfway through answering the 'why' part and realized I'd barely touched metrics.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a product improvement question on the Crisis Alert feature. Pretty focused session, just the one question but it had a lot of depth to unpack.
  • How would you improve Facebook's Crisis Alert feature?

“I went straight to user segments and started rattling off ideas before really anchoring on what the feature is actually trying to do.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview, got a product metrics question about Instagram Stories. Pretty standard for this type of role but it made me realize how much thought goes into picking the right north star.
  • You're the PM for Instagram Stories. What would you define as your North Star metric?

“I went with daily active users who post or view at least one Story, framing it around habitual engagement rather than raw view counts.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a product design question focused on a niche but interesting user segment. Pretty open-ended, which I wasn't fully prepared for.
  • Meta is looking to build a product for tradespeople such as plumbers and carpenters. How would you design it?

“I spent way too long on the user research framing and not enough time actually proposing features.”

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

May 2026
ML engineer system design round at Meta, one question about building a recommendation system. Pretty open-ended, which I wasn't fully prepared for.
  • Design a product recommendation system.

“I jumped straight into collaborative filtering and the interviewer just kind of waited.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview for the Groups team. One meaty question covering both product health measurement and experiment design for a specific feature. Pretty representative of what to expect if you're going for a data science role there.
  • What metrics would you use to assess the current health of Facebook Groups, and how would you design an experiment to evaluate a new comment-collapsing feature before rolling it out?

“Two questions stitched into one, which I didn't fully appreciate until I was already three minutes into talking about engagement metrics and the interviewer asked 'okay so what about the experiment.' I had to mentally restart.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round focused on debugging a friend recommendation validator. Pretty straightforward premise but there were enough edge cases to keep you honest.
  • You're given a buggy function that validates a list of recommended friends for a user. Fix it so it correctly rejects recommendations that include the user themselves, existing friends, or duplicate user IDs.

“The bug itself wasn't hard to spot once I actually read the tests.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

May 2026
Meta SWE coding round with an AI coding twist. The problem was finding three cards that sum to 15, broken into three parts: debug, implement, optimize. Spent too long on the bug hunt and had to lean on the AI to write the actual code for the later steps, but got through everything including follow-ups.
  • Given a set of cards, find three cards whose values sum to 15. The problem is broken into three parts: first identify a bug in provided code, then implement the algorithm from scratch, then optimize it.

“The bug-finding part ate up way more time than I expected.”

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

May 2026
Meta MLE system design round focused entirely on building a personalized recommendation system from scratch. It went deep fast and covered way more ground than I expected for a single session.
  • Design a large-scale personalized recommendation system. How would you frame the problem, define the objective, and decide what you're recommending to whom?
  • How would you handle data and labels for training the recommendation model, specifically around implicit vs explicit feedback, label noise, position bias, and delayed feedback?
  • Walk through your modeling approach: candidate generation versus ranking, and what are the failure modes of each?
  • How do you evaluate the recommendation system offline versus online, and how would you structure an A/B test to compare two models?
  • What are the key trade-offs you'd navigate: latency versus quality, exploration versus exploitation, and freshness versus stability?

“I jumped straight into modeling and the interviewer pulled me back: who is the user, what are we optimizing for, what counts as a good recommendation?”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta coding screen with a twist on a classic problem. Nothing crazy but the decimal handling tripped me up more than I expected.
  • Given two non-negative numeric strings that may include a decimal point, return their sum as a string without using any built-in numeric conversion functions. After computing the result, strip any trailing zeros from the decimal part.

“I knew the add-strings pattern going in, integer version is pretty standard.”

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