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Meta interview notes, page 43 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·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Got a product design question at Meta that seemed deceptively simple on the surface. Short round, one question, left feeling like I either nailed it or completely missed the point.
  • How would you design a toaster?

“I fumbled the opening by jumping straight into features without clarifying who the user even is.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Apr 2026
System design round at Meta for a software engineering role. The whole session was basically one big question about building an ad-click aggregation pipeline, and they went pretty deep on every layer of it.
  • Design a real-time ad-click aggregation pipeline that supports per-ad, per-advertiser, and per-geo aggregations over multiple time windows (1 minute, 1 hour, 1 day), with click deduplication and support for late-arriving events.
  • Walk through your non-functional requirements. How do you handle millions of QPS with low end-to-end latency, and what consistency guarantees are you targeting?
  • How would you design the ingestion path from the client click event all the way into your stream processor?
  • How would you implement the stream processing layer, specifically around windowing strategies and watermark handling?
  • What storage layer would you use for ad-hoc analytics queries on top of the aggregated data, and why?
  • How would you handle the split between a hot real-time path and a cold batch path, and when would you revert to the batch results?
  • How would you filter out fraudulent or invalid clicks in this pipeline?
  • How do you handle schema evolution in the event stream over time?
  • Do a rough capacity estimation for this system given millions of QPS.

“This was the whole interview, basically.”

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Meta·Data Scientist·Technical Phone Screen

Apr 2026
Meta DS interview that was basically a deep stats and monitoring design session. One long question broken into four parts, all around modeling comment count distributions and building alerting logic. Pretty intense for a phone screen.
  • Comment counts per post follow a heavy-tailed distribution with mean=4 and variance=50. How would you test whether a Poisson model is appropriate, and if it isn't, what would you propose instead and how would you estimate the parameters?
  • How would you compare the fit of a Poisson model versus a negative binomial or discrete lognormal, and what does each model capture differently about tail behavior?
  • Define robust monitoring metrics for comment counts (like trimmed mean, P50, Gini coefficient) and describe how you'd set control limits to detect manipulation such as purchased comments.
  • If the 99th percentile of comment counts suddenly jumps 3x but P50 stays flat, how would you design a rule to trigger an investigation while keeping false alarms low?

“The variance being way larger than the mean basically answers the Poisson question before you even run a test.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Meta SWE coding round with one meaty simulation problem. The question looks straightforward on the surface but the complexity discussion at the end is where things get interesting.
  • Given a non-negative integer array, simulate a repeated process: find the leftmost non-zero element, use it as a pivot value, walk rightward subtracting it from each subsequent element unless that element is smaller than the pivot, then add the pivot to a running total and repeat until no non-zeros remain. Return the total. Also discuss time complexity and potential optimizations over the naive simulation.

“The simulation itself wasn't too bad to code up once I nailed down the pivot behavior.”

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Meta·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Meta for a SWE role, just one question about manager conflict. Short and a bit awkward.
  • Tell me about a time you had a conflict with your manager.

“I had a story ready but it felt thin the moment I started telling it.”

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Meta·Data Scientist·Onsite - System Design / Architecture

Apr 2026
System design round at Meta for a Data Scientist role, which turned out to be way more infrastructure-heavy than I expected. The question was basically a distributed systems deep dive dressed up in a video-call context.
  • Design an admission-control system that enforces per-room participant limits across multiple distributed edge servers, where limits can change mid-call based on the host's subscription tier, and join/leave events may arrive out of order. You have 50ms to admit or reject a join request.
  • How would you propagate a mid-call limit change (e.g. the host upgrades from Free to Pro) instantly across all edges, and how do you fairly evict participants if the new limit is lower than the current occupancy?
  • How do you handle network partitions and cache layer failures in this system? Should you fail open (soft limit) or fail closed (hard rejection)?
  • How would you prevent the host bypass from exceeding global participant limits, and how do you detect drift between your counted occupancy and actual active media sessions?

“This one sprawled in every direction.”

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

Apr 2026
Brutal system design round at Meta for an MLE role. The question was a full notification ranking system from scratch, covering basically every dimension you can imagine. Left feeling like I'd done okay on the core ML parts but fumbled some of the operational stuff.
  • Design an ML-based ranking system for notifications sent to users, where candidates come from heterogeneous sources like product launches, friend activity, advertiser updates, and system messages.
  • How would you handle multi-objective optimization in this ranking system, balancing user engagement, advertiser revenue, and user fatigue?
  • Walk through how you'd construct training data for this ranker using click, dismiss, and conversion signals.
  • How would you control notification volume per user per day, and how does that interact with the ranking model?
  • How would you handle freshness and deduplication across notification sources?
  • How do you ensure fairness across notification sources, so that smaller or less-monetized sources aren't systematically suppressed?
  • Describe the serving stack: how do offline candidates flow into an online ranker and then get delivered to users?
  • What online metrics would you use to evaluate this system, and how would you think about long-term retention versus short-term CTR?

“This is the kind of question where you feel okay for the first ten minutes and then realize you've only scratched the surface.”

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Meta·Software Engineer·Technical Phone Screen

Apr 2026
Meta SWE coding round, one question on the classic trapped rainwater problem. Pretty standard but I second-guessed myself more than I should have.
  • Given an array of bar heights, calculate how much rainwater gets trapped between the bars.

“I knew this one but still fumbled the two-pointer approach explaining it out loud.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Meta system design round for a software engineer role. The whole question was basically 'build a competitive programming judge from scratch' and they wanted you to go deep on pretty much every layer of it. A lot of ground to cover in one session.
  • Design a competitive programming contest platform similar to LeetCode contests. Cover the full contest lifecycle, sandboxed code judging across multiple languages, real-time leaderboard at scale, anti-cheating measures, and surge handling when a contest starts.

“This is a beast of a question.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Meta PM interview with a single product design question about Facebook's birthday feature. Pretty open-ended, which I wasn't fully prepared for.
  • How would you design a birthday app for Facebook?

“I went straight to features and kind of skipped the 'why does this exist' part, which I regret.”

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