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Meta interview notes, page 203 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 - System Design / Architecture

Jun 2026
Meta SWE system design round, got asked to design a weather app. Not the most complex prompt but there's more to it than you'd think once you start pulling on the threads.
  • Design a weather application.

“Started with clarifying questions about scale and which features actually matter, which helped.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta product sense round, one question about designing for blood donation. Pretty open-ended and I kept second-guessing whether to go broad or pick a specific user flow and go deep.
  • Design a product that helps facilitate blood donations.

“I started with the supply side (donors) which felt right, but spent too long on awareness features and not enough on the actual friction points like scheduling, eligibility confusion, and post-donation follow-up.”

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Meta·Data Scientist·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Meta for a data scientist role, focused entirely on conflict, pushback, and stakeholder influence. Four prompts, all soft-skills territory, but they clearly wanted to see IC execution logic not just people-skills fluff.
  • Tell me about a time you had a conflict with a teammate and how you resolved it.
  • Describe a time you chose to push back on a project or analytical direction rather than just going along with it. What made you decide to push back instead of pivoting?
  • Walk me through a situation where you had to get a skeptical stakeholder or senior colleague to accept your recommendation.
  • Tell me about a time you had to work closely with someone who was difficult to work with. What did you do, and what happened?

“I had a decent story for this but I fumbled the ending.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Meta, one question about measuring discovery feature success. Pretty standard product metrics territory but the scope of Instagram makes it trickier than it sounds.
  • How would you measure the success of discovery features on Instagram?

“I went straight to engagement metrics and kind of forgot to define what 'discovery' even means first.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta product sense interview, one question about designing something for students during Covid. Pretty open-ended and I wasn't totally sure how deep they wanted me to go.
  • Design a product for students during Covid-19.

“My first instinct was to jump straight into features, which was a mistake.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Meta SWE coding round, one main algorithm question on merging sorted arrays with a follow-up on scaling it up. Pretty standard stuff but the k-array extension is where things got interesting.
  • Given three sorted integer arrays, merge them into one sorted array in O(n_a + n_b + n_c) time.
  • How would you extend this merge approach to handle k sorted arrays instead of just three?

“Three pointers, one per array, pick the smallest head each step and advance that pointer.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview with a product design question tied to the post-COVID travel boom. Single question, open-ended, and the kind of prompt that sounds easy until you're actually in it.
  • Given the surge in travel content and the post-COVID 'revenge travel' trend, design a new product for the travel space.

“I spent way too long on the context setup and not enough time on actual product decisions.”

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

Jun 2026
Did a design round at Meta for an ML Engineer role, focused on weapons advertising. The whole thing centered on data collection questions, and while AI tools were supposedly available, the interviewer never turned them on so that was kind of a non-factor.
  • How would you approach data collection for a weapons advertising system?

“This was the bulk of the round.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview, one question about Facebook reactions as a product metric case. Pretty standard product sense territory but the goal-setting angle made it a bit more specific than I expected.
  • How would you define a goal for Facebook reactions, and how would you measure success for that feature?

“I went straight to engagement numbers which felt like the obvious move but then got stuck on whether reactions are a proxy for something deeper like content quality or emotional resonance.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding screen, just the one problem about palindromes with a deletion allowed. Pretty standard stuff but worth knowing cold before you go in.
  • Given a string, can you determine if it becomes a palindrome by removing at most one character?

“Two pointer approach gets you most of the way there.”

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