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Meta interview notes, page 74 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·Technical Phone Screen

May 2026
Meta data scientist interview with a meaty fraud classifier case study. The whole thing was basically one long quantitative problem with a few conceptual layers stacked on top. Felt more like applied ML product design than a typical DS screen.
  • You have a credit card fraud classifier deployed as a probability scorer. Given a base fraud rate of 0.20% across 1 million transactions, and asymmetric costs of $15 per false positive and $100 per false negative, compute the expected TP, FP, FN, TN counts and total cost for three candidate thresholds. Which threshold minimizes cost and what are the business trade-offs?
  • How would you calibrate the model's probability scores, monitor for data or label drift over time, and periodically re-tune the operating threshold by segment such as country, merchant category, or transaction amount?
  • What guardrail metrics would you set up to catch harmful side effects like a spike in declines for high-value customers, and how would you design an experiment to validate threshold changes without causing serious customer harm?

“This is the kind of question where the math looks straightforward but you can fumble it fast if you mix up base rates.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a single product design question about museums. Pretty open-ended, which I wasn't fully prepared for.
  • Design a product for museums.

“I froze for a second because museums feel so far from Meta's core territory.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta software engineer interview with a mix of tree problems, dynamic programming, and string manipulation. Nothing too wild but the variety kept me on my toes.
  • Given a binary tree where each node contains a single digit, compute the total sum of all root-to-leaf numbers (where each path forms a multi-digit number).
  • Sort an array and return all indices where the target value appears.
  • In a binary search tree, find the node value closest to a given target.
  • Given a string with parentheses and letters, remove the minimum number of parentheses to make it valid.
  • Design a data structure that answers range sum queries on an immutable integer array efficiently.
  • You can climb one or two stairs at a time, each with a cost. Find the minimum cost to reach the top of the staircase.

“DFS felt like the right move and it was.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta software engineering interview with a mix of string manipulation and a sneaky math problem. The palindrome question felt approachable but the decimal addition follow-up was a different beast entirely.
  • Given a string, determine whether any permutation of its characters can form a palindrome. Follow-up: if such a permutation exists, generate and return one valid palindrome.
  • Implement addition of two non-negative numbers represented as strings, where either number may include a decimal point. You cannot use any built-in arbitrary-precision numeric types.

“The core check is straightforward once you realize a palindrome can have at most one character with an odd frequency count.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Meta DS interview with a SQL question centered on ad performance metrics. Pretty standard stuff for the role, but the details matter a lot here.
  • Given three tables (ads, impressions/clicks, and conversions), write a SQL query that returns impressions, clicks, conversions, CTR, and conversion rate for each ad and calendar date over the last 7 days. Order results by date and ad_id.

“The join logic is where I spent most of my mental energy.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE interview with a classic tree problem. Nothing too surprising but the follow-up directions they push you toward are where it gets interesting.
  • Given the root of a binary tree and two nodes p and q, find their lowest common ancestor.

“Got through the base recursive logic fine: return the current node if it matches p or q, recurse both sides, if both come back non-null you're at the LCA.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta coding screen, just the one question about palindromes. Pretty standard stuff but there's more to it than you'd think if you go in underprepared.
  • Given a string, find and return the longest palindromic substring.

“Knew the expand-around-center approach and coded it up fine, O(n^2) time.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a single product design question around Instagram. Short but deceptively open-ended, the kind of prompt that sounds easy until you realize how many directions it can go.
  • How would you design an art-focused product experience for Instagram?

“I went straight to user segmentation and probably spent too long there.”

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Meta·Software Engineer·Onsite - System Design / Architecture

May 2026
Meta system design round for a software engineering role. One question, classic streaming service prompt. Felt like it went okay but I kept second-guessing whether I went deep enough on the infrastructure side.
  • Design a streaming service similar to Netflix.

“I started with content delivery and worked backwards, which in hindsight was a weird entry point.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta software engineer interview, coding round focused on a frequency-based selection problem with a twist: they wanted you to walk through three different solutions in order of efficiency, not just jump to the optimal one. Felt like a trap for people who skip straight to the clever answer.
  • Given an array of integers and a value k, return any k elements that appear most frequently. Walk through a naive approach, a heap-based approach, and a linear-time approach, analyzing the trade-offs of each.

“The multi-part structure is what got me.”

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