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Meta interview notes, page 93 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 - Coding / Algorithms

May 2026
Three coding problems at Meta for a software engineer role. All algorithmic, all required complexity analysis on the spot. Nothing behavioral, just back-to-back problem solving.
  • Given the root of an N-ary tree and two target nodes, find their lowest common ancestor. If either node doesn't exist in the tree, return null.
  • You have two separately sorted lists of non-overlapping intervals. Merge them into a single sorted list with no overlapping intervals.
  • Given a list of lowercase words, find the largest subset where no letter appears more than once across all chosen words combined. Return the total character count of that subset.

“The null case is what trips people up here.”

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Meta·Software Engineer·Onsite - System Design / Architecture

May 2026
Meta system design round for a software engineering role, focused entirely on building a POI recommendation system from scratch. The question covered basically every layer of the stack and I was not fully prepared for how broad it would get.
  • Design a machine learning system that recommends places of interest to users, covering product goals, data sources, model architecture, training pipeline, serving infrastructure, exploration strategy, evaluation, and privacy considerations.

“This thing sprawled in every direction.”

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Meta·Machine Learning Engineer·Technical Phone Screen

May 2026
Technical screen at Meta for an ML Engineer role, focused almost entirely on LLM work. Two meaty topics: agent evaluation and post-training pipelines. The questions were specific enough that vague answers probably wouldn't fly.
  • Walk me through a recent project you worked on involving LLM agent evaluation. What tasks or benchmarks did you design, and what metrics did you use?
  • How did you address stochasticity in agent evaluation, and what did you do about judge bias when using an LLM as a judge?
  • Describe how you prepared or synthesized training data for an SFT or DPO pipeline. What were your sources, filtering criteria, and how did you handle deduplication and preference-pair construction?
  • What were the hardest challenges you faced in post-training, specifically around reward hacking, length bias, or evaluation flakiness?
  • How did you measure success in your post-training work, and what did a meaningful improvement actually look like?

“This one took up a lot of airtime.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Meta PM interview question about ad quality and trust and safety. Single question, product strategy flavor, no fluff around it.
  • You're a PM at Meta responsible for making sure no harmful or policy-violating ads appear across Meta's apps. What goals would you set and how would you measure whether you're succeeding?

“This one is deceptively wide.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
Interviewed for a PM role at Meta and got a product ideation question about Apple's next keynote announcement. Pretty open-ended, which I wasn't totally prepared for.
  • What product should Apple announce at their next keynote?

“I blanked for a second because it felt more like a bar trivia question than a PM interview.”

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Meta·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM case question at Meta, one of those strategy prompts where they drop you into a completely different industry and expect you to think through it cold. Just the one question but it had a lot of surface area.
  • You're a PM at Trader Joe's. Sales are declining in cities where Instacart and Blue Apron are active. How do you approach this?

“My first instinct was to jump straight into solutions, which was probably wrong.”

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Meta·Data Scientist·Technical Phone Screen

May 2026
SQL round at Meta for a DS role, one question but it had a few layers to it. The core was straightforward but the active ad definition tripped me up a bit.
  • Given an ads platform with tables for ads, impressions, and revenue events, write a SQL query that returns daily active ad revenue broken down by creation source. An ad counts as active on a day if it received at least one impression that day, and revenue should only be summed for those active ads on that same day. Include distinct active ad count and total revenue per day per source, ordered by date and source.

“The join structure took me a second to get right.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding question focused on parentheses parsing. Pretty standard algorithmic problem but the edge cases around unbalanced strings are where things get interesting.
  • Given a string that may contain parentheses and other characters, write a function to return the maximum nesting depth of balanced parentheses. If the parentheses are unbalanced, return -1.

“My first instinct was to just track depth with a counter and update the max as I go.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

May 2026
Did a Meta SWE coding round that had multiple levels of difficulty, each adding more constraints on top of the last. Made it through the earlier parts okay but Level 3 introduced timestamp and TTL requirements and I just couldn't get through all the test cases in time.
  • Implement a series of cache-like functions that support timestamp tracking and time-to-live (TTL) expiration logic.

“The earlier levels were manageable but once TTL came into the picture I slowed way down.”

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Meta·Software Engineer·Technical Phone Screen

May 2026
Meta SWE coding round with a classic heap problem, though the N >> k constraint is what makes it interesting and what they're actually testing for.
  • Given a large integer array of length N and an integer k where N is much larger than k, find the k largest elements. You don't need to return them sorted, but you should use an approach suited for the N >> k case.

“The key thing they're probing is whether you reach for a min-heap of size k instead of sorting the whole array.”

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