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Meta interview notes, page 169 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·Onsite - Coding / Algorithms

Jun 2026
Meta software engineer coding round, three algorithm questions back to back, all variations on the same theme of increasing sequences. Felt like a gauntlet. The grid one at the end really tested whether you knew your graph traversal cold.
  • Given an integer array, find the longest strictly increasing contiguous subarray. Return the length and start/end indices. Target O(n) time and O(1) space. How do you break ties when multiple subarrays share the same maximum length?
  • Compute the length of the longest strictly increasing subsequence in an integer array and reconstruct one valid subsequence. Aim for O(n log n) time with O(n) space. Explain the data structures involved and why the approach is correct.
  • Given an m x n grid of integers, find the length of the longest strictly increasing path where each step moves to one of the four orthogonal neighbors. Optionally return one such path. Grid can be up to 500x500. Design the algorithm and analyze time and space complexity, including how you prevent revisiting states.

“Easiest of the three.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Meta, product strategy question framed around the gaming console space. Single question but it went pretty deep into both the build rationale and how you'd define success post-launch.
  • You're a PM for a gaming console. Make the case for building the next-generation version, and explain how you'd measure whether it was a success.

“The build justification part felt manageable.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta data engineer interview with a coding question around array manipulation. Pretty standard algorithmic problem but worth knowing cold if you're prepping for this role.
  • Given a sorted array of integers, return a new sorted array of the squares of each element.

“The naive solution is just square everything and sort again, which works but they clearly wanted better.”

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

Jun 2026
ML system design round at Meta for an MLE role. The whole thing was basically one big question about building a short-video recommendation system from scratch, and they wanted you to go deep on almost every layer of it.
  • Design a personalized short-video recommendation system similar to TikTok. Walk through functional requirements, the data pipeline, candidate generation, ranking, and how you'd handle cold start and latency constraints.
  • How would you structure the offline and online evaluation strategy for this recommendation system?
  • How do you balance exploration versus exploitation in a recommendation feed where you also need to keep users engaged?
  • What are your strategies for handling cold start for both new users and new content creators on the platform?
  • How would you design the system to meet strict latency requirements while still running a complex multi-stage ranking pipeline?

“This is a beast of a question and I underestimated how much they'd want to go into each layer.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE interview with a valid parentheses problem. Pretty standard coding round, nothing that would surprise anyone who's done leetcode prep.
  • Given a string of parentheses (and possibly other bracket types), determine whether the string is valid, meaning every opening bracket has a corresponding closing bracket in the correct order.

“Stack-based solution, pretty much what you'd expect.”

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Meta·Data Scientist·Onsite - Product Sense / Strategy

Jun 2026
Meta DS onsite with a meaty open-ended case on rolling short video into a social newsfeed. Covered metrics, data modeling, and experiment design all in one question, which felt like a lot to juggle in real time.
  • How would you define the goal metrics and guardrails for rolling out short video into a social platform's newsfeed?
  • Design a data model for a platform where Content can be text, image, or video, and users interact with that content in various ways.
  • How would you measure the impact of introducing short video to the newsfeed, including A/B test setup, user segmentation, and any secondary effects to watch for?

“I went straight to engagement and time spent, which felt right, but I fumbled a bit on the guardrail side.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta data/analytics interview, one SQL-heavy question that sounds straightforward until you actually try to write it out. The join logic for detecting active rentals on a specific date is the part that trips people up.
  • Given a rentals table with start and end dates and a cars table with location and size info, write a query to find, as of a specific date, how many cars are currently rented out per city and car size, the total stock for each city/car size combination, and the ratio of rented to total stock.

“The ratio part is almost decorative, it's just a division at the end.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview focused entirely on Workplace Chat, which made sense in hindsight but felt weirdly narrow in the moment. Three connected questions that kept building on each other.
  • Why do you think Meta chose to invest in building Workplace Chat?
  • How would you define success metrics and set goals for Workplace Chat?
  • If the number of users sending messages drops but total message volume goes up, what might explain that?

“I went straight to the obvious stuff about enterprise revenue diversification and competing with Slack, but I kept second-guessing whether they wanted a more internal-Meta angle.”

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Meta·Data Scientist·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round for a Data Scientist role at Meta, covering the usual teamwork and self-reflection territory. Nothing technically surprising, but the questions pushed harder on specifics than I expected.
  • What was the biggest challenge you faced on a recent project, and how did you work through it?
  • Tell me about a time you gave constructive feedback to a teammate. How did you deliver it, and what happened afterward?
  • How do you actively build trust when working across different teams or functions?
  • Describe a time you had a conflict or disagreement at work. What did you do, and what did you take away from it?

“I had a decent story ready but fumbled the 'how you overcame it' part.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview with a product design question tied to a real-world event. Pretty open-ended, which I wasn't fully prepared for.
  • You're on the LA 2028 Olympic Games organizing committee. What product would you build?

“I fumbled the opener because I tried to pick something clever instead of just grounding myself in who the users actually are.”

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