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Meta interview notes, page 48 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·Data Scientist·Onsite - Behavioral / Leadership

Apr 2026
Behavioral prep material for a Meta Data Scientist product analytics loop. All four questions are the classic people-and-process type, nothing technical, so if you're hoping for SQL or stats you'll be disappointed by this post.
  • Tell me about a breakthrough project you worked on. What made it a breakthrough, why did it matter, and what specifically did you contribute?
  • Describe a time you disagreed with a teammate, cross-functional partner, or manager. How did you handle it and what was the outcome?
  • A new manager or stakeholder joins who has no historical context on your team's work. How do you communicate with them and build trust over time?
  • How would you help a new teammate get up to speed and feel welcome on the team?

“This one sounds easy until you realize 'breakthrough' is doing a lot of work.”

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Meta·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Got a coding question for a Meta ML Engineer role that was more tree traversal than anything ML-related. Pretty standard algorithmic problem, nothing too surprising.
  • Given the root of a binary tree where each node holds a value from 0 to 25 (mapping to letters 'a' through 'z'), find the lexicographically smallest string that can be formed by reading a path from any leaf up to the root.

“The path goes leaf-to-root but the string reads that direction, so you have to think about it carefully or you'll build the string backwards and not realize it until you're comparing.”

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Meta·Product Manager·Onsite - Behavioral / Leadership

Apr 2026
Behavioral screen for a PM role at Meta, just the one question but it felt like they were really trying to poke at what actually drives you versus what sounds good.
  • Tell me about a time you worked on something you were genuinely passionate about.

“I fumbled this more than I expected.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Meta SWE coding round with a trie-style problem. The core task was building a word container that handles prefix queries efficiently, and the whole point was that brute force wasn't going to cut it.
  • Design a data structure that supports two operations: adding a word to a container (duplicates are fine to ignore), and querying whether any stored word is a prefix of a given string. The brute force scan-all approach won't pass within the constraints.

“My first instinct was to just iterate through all stored words and check prefix for each query, which is obviously what they told you not to do.”

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Meta·Software Engineer·Technical Phone Screen

Apr 2026
Meta coding round, one algorithmic problem the whole session. The question was a bitmask DP problem I'd seen before but still had to think through carefully under pressure.
  • Given a list of words, find the largest subset such that no letter appears more than once across all chosen words combined. Return the maximum total character count.

“I knew this problem, which helped, but I still fumbled explaining the bitmask approach cleanly at first.”

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Meta·Software Engineer·Technical Phone Screen

Apr 2026
Meta SWE coding round with a classic selection problem. Nothing too wild but the 0-indexed twist on k-th largest is the kind of small detail that'll bite you if you're not paying attention.
  • Given an integer array and a 0-indexed integer k, return the k-th largest element in the array (so k=0 means the maximum, k=1 means the second largest, etc.).

“The 0-indexed part is what gets people.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Meta, product sense round focused on Facebook Events. One meaty question that pushed both the 'why build it' angle and the metrics side, which is a lot to cover in one prompt.
  • You're the PM for Facebook Events. Make the case for why Meta would build this product, and define the metrics you'd use to track whether it's succeeding.

“The 'why build it' part felt easier since you can tie it to social graph engagement, ad inventory, local discovery.”

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Meta·Software Engineer·Technical Phone Screen

Apr 2026
Meta software engineering interview with a classic array manipulation problem. The follow-up caught me more off guard than the main question, which I didn't expect.
  • Given a sorted non-decreasing array of integers, modify it in-place so each distinct value appears exactly once, preserving order. Return the new length of the valid prefix, and justify that your solution runs in O(n) time and uses O(1) extra space.
  • Modify your previous solution so that each value may appear at most twice instead of exactly once. Walk through what changes and why.

“Two-pointer approach clicked pretty fast.”

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Meta·Data Scientist·Technical Phone Screen

Apr 2026
Meta DS interview focused entirely on a local SMB ads product case. Three questions, all connected to the same scenario, which made it feel more like a product sense loop than a traditional DS screen.
  • How would you define a 'local business' for the purpose of Facebook ads targeting?
  • If small businesses are boosting their popular posts, what metric would you use to measure whether that's actually working?
  • You're running an experiment and CTR on boosted posts comes back lower than expected. Walk through your hypotheses and how you'd validate them.

“I started rattling off things like physical storefront, zip code radius, employee headcount.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Meta system design interview, one question about deduplicating school entities on the platform. Pretty open-ended and I wasn't totally sure how deep to go on the data side versus the product side.
  • Design a system to detect and filter duplicate school entries on Facebook.

“I started with fuzzy string matching on school names and then realized there's a whole mess of location data, alternate names, and user-generated variations to deal with.”

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