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Meta interview notes, page 162 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·Technical Phone Screen

Jun 2026
Meta SWE coding round, one question the whole time. The problem was a subset selection thing where you maximize unique letter coverage without any letter appearing twice across chosen words. Harder than it sounds once you start thinking about the combinatorics.
  • Given a list of words, find a subset where no letter appears more than once across all chosen words, and the total number of distinct letters covered by the subset is as large as possible.

“My first instinct was greedy and it was wrong.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta data scientist interview with a product-focused question on push notification quality. One question, but it had a lot of moving parts and I felt like I only half-covered what they were looking for.
  • A product team wants to improve push notification quality. What data sources would you use to design and deliver better notifications, what metrics would you track to measure success, and how would you quantify any negative impact from sending them?

“I went straight to engagement metrics and kind of forgot to anchor on the data sources first, which I think threw off the flow.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round with a grid traversal problem. Pretty classic BFS setup but the way they framed it with the move/canMove abstraction threw me off a bit at first.
  • Given a 2D grid maze with a start position and a cheese position, implement move() and canMove() functions and find the shortest path from start to cheese. Return -1 if no path exists.

“The abstraction layer with move() and canMove() is what made this feel different from a plain BFS grid problem.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta DS interview with a product experimentation case built around Instagram. The whole thing was one big scenario about a feature that hadn't launched yet, so you had to work entirely from proxy logic and experimental design. Pretty intense for a single question but it covered a lot of ground.
  • Instagram is thinking about adding a 'Show similar products' button. Before it launches, how would you convince a PM it's worth building, and what existing data would you use to estimate its potential impact on engagement?
  • How would you design an experiment to decide whether to launch the 'Show similar products' button, including your randomization unit, what the control and treatment look like, and what guardrail metrics you'd set?
  • What criteria would tell you it's safe to roll out the feature to everyone?

“This part tripped me up more than I expected.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Meta, one question focused on the Verified Badge product. Pretty strategic, no behavioral fluff, just jumped straight into a product case.
  • You're the PM for Meta's Verified Badge. Why would Meta build this product, and how would you define goals and success metrics for it?

“I started with the business rationale side and it felt okay, talked about trust, creator monetization, distinguishing real accounts from impersonators.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta coding round for a software engineer role, two problems back to back. Nothing too exotic but the second one has more moving parts than it looks like on the surface.
  • Given a word and an abbreviation string, determine whether the abbreviation is valid for that word. Digits represent skipped characters, no leading zeros allowed, and digit sequences can't be empty.
  • Given a reference to one node in a connected undirected graph, return a deep copy of the entire graph.

“Two pointers, one on each string.”

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Meta·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Meta business analyst interview with a market expansion case question. Pretty standard go/no-go framing but the breadth of what they expected you to cover was wider than I anticipated.
  • We're thinking about launching in a new city. What data would you look at to make a go or no-go recommendation?

“I started with market size and TAM stuff which felt safe, but then I blanked a bit on the operational side.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview with a product design question about podcast recommendations. Pretty open-ended, which sounds fun until you're actually sitting there trying to figure out where to start.
  • Design a product that provides podcast recommendations to users.

“I jumped straight into user segmentation and probably spent too long there.”

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Meta·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Meta coding round for an MLE role, one problem the whole session. They gave me an existing maze traversal implementation and asked me to extend it with directional cell constraints. Felt manageable at first but the edge cases piled up fast.
  • You're given an existing maze traversal solution with a move(from_cell, to_cell) method. The maze now includes directional cells ('>' for left-to-right only, '<' for right-to-left only). Modify only the move method to enforce these directional constraints, and walk through edge cases like starting on a directional cell, two adjacent conflicting directional cells, and how this change interacts with the BFS/DFS caller.

“The base problem clicked pretty fast, checking the direction of movement against the cell marker is just arithmetic on coordinates.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta DS interview with a product metrics question centered on their notification survey feature. The question had a lot of moving parts and I felt like I was barely keeping up with all the angles they wanted covered.
  • For Meta's in-app survey feature triggered after notifications, define a primary goal metric, at least one driver metric, and at least one guardrail metric. Then explain how you'd account for network effects and novelty effects when interpreting those metrics.

“The metric definitions felt manageable at first.”

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