Meta interview notes, page 155 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·Online Assessment (OA)

Jun 2026

Meta DS interview, technical phone screen or OA style, one big SQL problem covering cohort analysis with a bunch of edge cases baked in. The schema was realistic and the question had enough gotchas that you couldn't just wing it.

Given a multi-table schema (users, events, orders, payments, refunds), write a single SQL query that produces one row per signup cohort month for August 2025, reporting active users, payers, payer rate, and GMV. The query must handle invalid payments, same-month refunds that cancel out a payer, late payments landing outside the month, a NULL-safe denominator, and NULL user_ids.

“This one took me longer than I expected to outline before writing a single line.”

View Post

Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

Did a product sense round at Meta for a PM role. Pretty standard vibe, one question, not much to report.

What is your favorite product and why?

“Blanked for a second on which product to pick.”

View Post

Meta·Data Scientist·Technical Phone Screen

Jun 2026

Meta DS interview focused on a product launch scenario for a scheduled posts feature. The whole thing was a mix of stats and product sense, which I wasn't fully expecting to be so intertwined in one session.

How would you define and estimate the failure rate of scheduled posts using a Bayesian approach? Assume a failure means the system didn't publish the post within 5 minutes of the scheduled time, and the user didn't cancel it.
From a product perspective, how do you decide whether the scheduled posts feature is actually successful after launch?
What experiment would you design to test this feature, and which metrics would you track?
What biases, confounders, or edge cases would you watch out for when evaluating this feature?

“This was the part I was least prepared for.”

View Post

Meta·Software Engineer·Technical Phone Screen

Jun 2026

Meta coding interview, just the one question about longest increasing subsequence. Not much to go on but it's a classic that'll humble you if you're not warmed up on DP.

Find the longest increasing subsequence in an array.

“Classic DP problem but the O(n log n) patience sorting approach is where people trip up.”

View Post

Meta·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026

Interviewed for an EM role at Meta. One behavioral question, felt like a standard leadership principles screen.

Describe a time you made a bold or difficult decision.

“Classic behavioral question but it still tripped me up a little.”

View Post

Meta·Machine Learning Engineer·Technical Phone Screen

Jun 2026

Meta ML engineer interview with a pretty meaty algorithms question about sliding window medians. One round, heavy on complexity analysis and edge case handling. Left feeling okay about the approach but not totally confident on the even-k median definition.

Given an array and an integer k, return the median of every contiguous subarray of length k. Your solution should run in O(n log k) time, handle duplicates and deletions correctly, and you need to define what median means when k is even. Also analyze space complexity.

“This is the kind of question where the basic idea clicks fast but the details wreck you.”

View Post

Meta·Software Engineer·Technical Phone Screen

Jun 2026

Meta Data Engineer coding round, one algorithmic problem that looked deceptively simple but had a neat counting trick hiding underneath it.

Given an integer array of length n, count the number of index pairs (i, j) where i < j, the product of the two elements is even, and the difference in indices is odd.

“I started brute-forcing it in my head and then caught myself.”

View Post

Meta·Software Engineer·Technical Phone Screen

Jun 2026

Did a technical phone screen for a Software Engineer role at Meta. One coding question, classic interval merging problem. Nothing too wild but it's the kind of thing that punishes you if you skip the sorting step.

Given a list of closed intervals, write a function that merges all overlapping intervals and returns a list of non-overlapping intervals covering the same ranges.

“Sort by start time first, that's the whole trick.”

View Post

Meta·Data Scientist·Technical Phone Screen

Jun 2026

Meta data scientist interview with a set of CS fundamentals questions covering data structures back to back. Pretty straightforward if you've reviewed your basics, but the time complexity justifications tripped me up a bit.

Describe the data structure where each node has at most two children and one parent. What fields does each node typically hold, and if keys are stored for ordered searching, what are the average and worst-case search times and what condition must hold to achieve the average case?
Name the data structure where each element points to the next and supports O(1) insertion at the head. How do you detect a cycle in it, and what are the time and space complexities of your approach?
For an unsorted array of n integers, what is the worst-case time to check if a target value exists? If sorted, what algorithm would you use and what is the new complexity? And is binary search valid on an unsorted array?

“Binary search tree, obviously, but I fumbled explaining why average case is O(log n) specifically because of the balanced property requirement.”

View Post

Meta·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Meta software engineering coding round, four questions back to back. Nothing too exotic but the pacing was real and a couple of them had wrinkles I didn't see coming until I was already mid-solution.

Given a string with lowercase letters and parentheses, remove the minimum number of characters to make the parentheses valid. Return any valid result.
Find the lowest common ancestor of two nodes in a tree where each node has a parent pointer.
Compute the depth-weighted sum of a nested integer list, where each integer is multiplied by its depth level (top-level is depth 1).
Return the K closest points to the origin from a list of 2D points.

“Two-pass approach: left to right tracking unmatched closing parens, right to left for unmatched opens.”

View Post