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Meta interview notes, page 147 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

Jun 2026
Meta PM interview, product sense round focused on Instagram Stories. Single question but it had a lot of surface area and I don't think I covered it as well as I should have.
  • You're the PM for Instagram Stories and are evaluating whether to extend the 24-hour expiration window. What metrics would you look at to make that decision?

“I jumped straight into engagement metrics and kind of forgot to frame why the 24-hour limit exists in the first place.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Meta system design round for a software engineer role. One question, but it had a lot of moving parts and they definitely pushed on the implementation details more than I expected.
  • Design and implement a fixed-capacity in-memory cache with get and put operations that run in average O(1) time. When the cache is full, evict the least-recently accessed item. Walk through your data structure choices, how you track access order on reads and writes, and analyze the time and space complexity. Then write the core code.

“I knew this was an LRU cache question the second they said it, which honestly made me a little overconfident.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta DS interview for what looked like a product analytics role. One big open-ended question about a notification feature on a C2C marketplace, covering everything from pre-launch framing to post-ship experiment design. Pretty exhausting to get through in one sitting.
  • You're a DS on a C2C marketplace app. The team wants to add a feature where buyers can opt into notifications for similar listings. Before building anything, how would you decide if this is even worth pursuing? Walk through the user problem, what metrics you'd expect to move, the risks involved, any pre-build data analysis you'd do, and how you'd structure a phased rollout.
  • Assume the feature has been shipped and can be enabled for a subset of users. How do you design the experiment to measure its impact? Be specific about randomization unit, control vs treatment, duration, your primary and guardrail metrics, and how you'd handle issues like opt-in bias, interference, and attribution.

“This part went okay but I spent way too long on the metrics taxonomy and not enough on the pre-build validation angle.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta DS interview focused entirely on product analytics for a new social groups feature. Three questions, all interconnected, and the retrospective analysis one genuinely tripped me up mid-answer.
  • What metrics would you use to measure the success of Circle (Meta's new group-based social feature)? Define a primary north-star metric and the supporting metrics around it.
  • Using only observational (non-experimental) data, how would you determine whether Circle should be optimized for small private groups or large public groups?
  • You're shown time-series charts of total comments divided by total posts for three different products with different user bases. Can you directly compare these lines across products?

“I went straight to DAU and immediately knew that was wrong the second I said it.”

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Meta·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Meta for an Analytics Engineer role, all four questions were collaboration and process focused. Nothing technical, which I wasn't fully expecting going in.
  • Tell me about a time you worked with people from very different backgrounds or perspectives. How did you make sure everyone had a voice and decisions still got made?
  • Describe a situation where a teammate's working style clashed with yours. How did you handle it and what came out of it?
  • Share an example of giving or receiving difficult feedback. How did you approach the conversation and what actually changed as a result?
  • Tell me about a time when documentation (or the lack of it) had a real impact on a project. What did you do about it?

“I had a decent story here but rambled too long on the context and barely got to the outcome before they moved on.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Product sense round at Meta for a PM role. One big open-ended question about Apple's future product roadmap, which sounds fun until you're actually sitting there trying to justify a fictional device to someone who clearly has opinions.
  • Design a new Apple product that could be announced 5 to 6 years from now. What features would it have, and how would it fit into the existing Apple ecosystem?

“I went straight into feature brainstorming and kind of skipped the 'why does this product exist' part, which I regretted about three minutes in.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Meta, one question about measuring success for a new product launch. Pretty focused session, no fluff.
  • As a PM at Meta, how would you define and measure the success of launching a job marketplace?

“I went straight for engagement metrics and kind of forgot to set up the context first.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Meta SWE system design round focused on distributed web crawling at massive scale, with a variant framing it as a flight price aggregator. The design space was deep and the follow-ups kept coming.
  • Design a distributed web crawler that can handle billions of URLs per day at Meta scale.
  • How would you handle deduplication across billions of crawled pages?
  • Walk me through your storage choices for the crawled HTML and metadata.
  • How would you extend your crawler to handle JavaScript-rendered pages?
  • How do you handle hot shards in your distributed crawler design?

“This is the core question and it's deceptively broad.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview with a product evaluation question about Instagram Stories. Pretty standard product sense round, though this type of question has more surface area than it looks.
  • How would you evaluate whether Instagram Stories has been a success?

“I went straight to engagement metrics and kind of forgot to anchor on what 'success' even means for a feature like this.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round with a tree traversal problem. Nothing too wild but the constraints tripped me up more than I expected.
  • Given a binary tree, find the longest continuous downward path where each node's value is strictly increasing. The path can start and end at any node. Output the node values space-separated.

“Spent the first few minutes just re-reading the input format because it's given as parent-child pairs rather than a typical tree structure, so you have to build the tree yourself first.”

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