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Meta interview notes, page 167 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·Technical Phone Screen

Jun 2026
Meta coding interview with a debugging twist. Instead of writing something from scratch, they handed me broken code and asked me to find what was wrong with it.
  • You're given a maze-solving function that's already written. When it prints the path, it's including cells that shouldn't be walkable. Find the bug and fix it.

“Took me longer than I'd like to admit to stop reading the recursion logic and just focus on what was being printed.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round, one problem the whole time. A binary search variant that looks deceptively familiar if you've done LC 162, but flipped to find a valley instead of a peak. Felt okay about it but I'm never fully sure with Meta.
  • Given an integer array, find any index where the element is strictly less than both its neighbors (a local minimum / valley). Treat out-of-bounds neighbors as positive infinity. Solve it in O(log n) using binary search.

“I recognized the peak-finding pattern pretty fast, which was both helpful and a little dangerous.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round focused on linked list manipulation, specifically deep copying a list with random pointers. Two solutions were expected back to back, which I wasn't fully prepared for.
  • Given a linked list where each node has both a next pointer and a random pointer, implement a deep copy of the list. Start with an O(n) time, O(n) space solution using a hash map, then optimize to O(1) extra space by interleaving copied nodes with the originals.

“I got the hash map version out pretty cleanly.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Meta software engineer coding round with two algorithm problems. Both had a brute-force-then-optimize structure which I kind of expected, but the second one tripped me up more than I'd like to admit.
  • Given a list of integers, find the indices of any three distinct elements that sum to 15. Discuss edge cases, a brute-force approach, and an optimized solution.
  • Given a list of lowercase words, find the maximum length of a concatenation of any subset where the final string has no repeated characters. Words with internal duplicates cannot be used.

“Started with the O(n^3) triple loop which they were fine with as a starting point.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
A deep causal inference case for Meta DS, focused on designing a study around parental account linking for teens. The question was massive and covered basically every angle of experimental design you can think of. Felt more like a take-home than a live interview.
  • Meta wants to let parents register and link to their teen's account. Design a study to estimate the causal effect of parental registration on teen well-being and engagement. Cover metrics, experimental design, power, measurement, validity threats, a quasi-experimental fallback, and ethics.

“This was a monster.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta software engineering interview with two coding problems back to back. The second one had a follow-up that I did not see coming.
  • Given a binary search tree and a target value, find the node value in the tree that is closest to the target.
  • Given a string with parentheses, remove the minimum number of parentheses to make it valid. Follow-up: can you do it without using a stack?

“Pretty standard BST traversal problem.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Got a Meta coding screen with a sliding window problem. Pretty standard stuff, nothing too wild.
  • Given an integer array and an integer k, find the contiguous subarray of length k with the maximum average value and return it.

“Classic sliding window, you compute the sum of the first k elements then slide across the array updating the sum as you go.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
A deep technical screen for a data scientist role at Meta, centered entirely on one massive experiment design question about a spam detection feature for Messenger. The level of detail expected was genuinely surprising, covering everything from cluster randomization math to launch ramp plans.
  • For a new spam-detection algorithm on Messenger that routes suspected spam to a separate folder and delays delivery, define your primary success metric and at least three guardrail metrics. Be specific about denominators and attribution windows.
  • Compare individual-user randomization versus cluster randomization by conversation thread, by recipient, and by geography for this experiment. For each, walk through how interference could occur and when SUTVA breaks down.
  • What are the specific pitfalls of cluster randomization designs, and how would you mitigate them in this context?
  • Given a baseline spam reply rate of 2%, a target of detecting a 10% relative reduction, alpha 0.05, power 0.8, and a 7-day test window with 200M suspected-spam messages per day: compute the design effect and effective sample size for thread-level clustering with average 3 messages per thread and ICC of 0.07. Then repeat for recipient-level clustering with 20 messages per recipient and ICC of 0.02. Which design do you recommend?
  • Describe your full analysis plan: which estimator, how you handle inference, whether you'd use CUPED, and how you'd deal with noncompliance or multiple exposure types.
  • Given effect sizes in the range of minus 8 to minus 12 percent relative reduction on spam reply rate with guardrails holding, what is your quantitative launch criterion and what does your ramp plan look like?

“Went with spam reply rate as the primary metric, which felt right, probability a recipient replies within 24 hours to a flagged message.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Interviewed at Meta for a role that involved evaluating the difficulty of a Duolingo language test. Not a lot of detail to go on here, but it seemed like a product sense or analytical exercise.
  • How would you assess the difficulty level of a Duolingo language test?

“This is a deceptively open question.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta coding round for a software engineer role. One design question about building a data structure with two operations, nothing too wild but it took me a bit to think through the sliding window angle.
  • Design a class that supports two operations: adding a value to a list, and computing the product of the last k elements.

“Took me a second to realize the naive approach of just multiplying the last k elements each time is fine for small inputs but they clearly wanted something better.”

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