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Meta interview notes, page 107 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 modeling question about predicting engagement uplift for a new product feature. One question, but it had a lot of moving parts and they clearly wanted to see end-to-end ML thinking.
  • How would you build a model to predict whether a new 'Show similar products' button increases buyer engagement, covering feature selection, algorithm choice, sample size, evaluation, and how you'd translate results into a launch recommendation?

“This is the kind of question where you can spiral if you try to answer everything at once.”

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Meta·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at Meta for a software engineering role. The prompt was a full-blown notification platform design covering basically every subsystem you can think of. Felt like three questions crammed into one.
  • Design a push notifications and in-app messaging platform for a large consumer mobile app. Cover user preference management, segmentation and targeting, deduplication, rate limiting, retries and backoff, idempotency, scheduling and batching, A/B experiments, and localization. Describe the APIs, data model, event pipeline, delivery workers, and integration with iOS and Android push services.
  • How would you handle scalability to millions of daily active users, multi-region deployment, and the trade-offs between consistency and availability in this notification system?
  • How would you approach monitoring and alerting, GDPR and CCPA compliance, and failure handling for this platform?
  • Walk through your capacity estimates and propose a rollout plan for launching this platform.

“The scope was overwhelming at first.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Second problem in a Meta SWE phone screen loop, and it was the one that apparently filters most people out. The sliding window stuff sounds manageable until you're actually writing it under pressure.
  • Given two strings s and t, find the shortest substring of s that contains all characters of t (including duplicates). Return an empty string if no such substring exists.

“The part that tripped me up wasn't the expand-right logic, it was the matched counter.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta product design interview, one question about building a spreadsheet experience for mobile. Pretty open-ended and I spent the first few minutes just trying to figure out what angle they actually wanted.
  • How would you design a spreadsheet application for mobile phones?

“I went straight to the UI constraints and probably should've started with the user first.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta data engineer technical screen, just one SQL problem but it had enough layers to keep me busy for a while. The car rental utilization question looked straightforward on the surface but the edge cases around overlapping intervals and NULL dropoff timestamps slowed me down more than I expected.
  • Given tables for users, locations, cars, and rentals, write a SQL query that computes for each city and car size combination: the number of distinct cars rented on a specific date, the total active inventory for that city and car size, and the utilization rate as a decimal. Handle the case where a car has not yet been returned (NULL dropoff) and avoid dividing by zero.

“The join structure wasn't the hard part.”

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Meta·Machine Learning Engineer·Technical Phone Screen

May 2026
Meta ML engineer interview, coding round focused on probability and sampling. The follow-up question is what really separates people who've thought about production scale from those who haven't.
  • Given an array of weights, implement a function that randomly samples an index with probability proportional to each weight. Then, if this function is called millions of times, how would you optimize it?

“The prefix sum plus binary search part came together fine, O(log n) per query, not too bad.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
Product-focused DS interview at Meta centered entirely on notification quality metrics and experiment design. No coding, just a two-part case that went deeper than I expected once the follow-ups started rolling in.
  • What data would you look at to decide whether a notification is 'high-quality'? Think both immediate signals and longer-term ones, and consider how you'd segment.
  • Propose a primary success metric for notification quality, plus diagnostic metrics and guardrails. Define each one precisely.
  • Design an experiment to evaluate a new geographic notification feature (e.g. 'A concert is happening near you tonight'). Cover treatment vs control, randomization unit, and how long you'd run it.
  • What are the main threats to validity in this geo notification experiment, and how would you address them?
  • Short-term engagement goes up but opt-outs and mutes also increase. What do you conclude and what do you recommend?

“I started with the obvious stuff: open rates, dismiss rates, mute/disable events.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta coding round focused entirely on a string DP problem. Nothing behavioral, just one meaty algorithm question with a bunch of follow-ups on optimization. Left feeling okay but not great.
  • Given a string and an integer k, can the string be turned into a palindrome by deleting at most k characters? What is the minimum number of deletions needed, and how does your algorithm determine whether that minimum is within k?

“This is a classic longest palindromic subsequence reframing and I knew that going in, which helped.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Interviewed for a PM role at Meta and got asked about the Portal product. Short and focused, not much else to report.
  • Why did Facebook build the Portal?

“Had to think through the strategic rationale from Facebook's perspective, not just what the product does.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview with a product analytics question about funnel optimization. Pretty short session from what I can tell, just the one question but it had some teeth to it.
  • You have a multi-step funnel with drop-offs happening at every stage. Which stage do you tackle first, and why?

“My instinct was to say the stage with the highest drop-off rate, which felt obvious the moment I said it out loud.”

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