Meta Interview Questions

Meta System Design Interview Questions

Practice 1,159 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable impact.

1.2k Questions 1 Company07.06.2026
Showing 20 results
Role
Meta logo
Meta
Hard
Data Scientist Locked

Design an Experiment to Evaluate New Recommendation Model

This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a rea...

Analytics & Experimentation
138
2
374 people solved
Aug 4, 2025
Meta logo
Meta
Medium
Data Engineer

Check carpool trip feasibility

You are given a list of trips where each trip i is (passengers_i, start_i, end_i) with start_i < end_i on a one-dimensional route. A single vehicle wi...

Coding & Algorithms
6
0
77 people solved
Aug 1, 2025
Meta logo
Meta
Medium
Data Engineer

Compute cumulative metrics with full joins

Tables: - daily_metrics(date DATE, content_id STRING, daily_value BIGINT) - cumulative_metrics(date DATE, content_id STRING, cumulative_value BIGINT) ...

Data Manipulation (SQL/Python)
0
0
8 people solved
Aug 1, 2025
Meta logo
Meta
Medium
Data Engineer

Return top-3 content per category

Given a collection of items with fields (content_id, category, rating), implement top_k_by_category(items, k= 3) that returns, for each category, the ...

Data Manipulation (SQL/Python)
1
0
3 people solved
Aug 1, 2025
Meta logo
Meta
Easy
Data ScientistSenior+

Compute invalid event percentage by pixel

Context You work on an ads pixel instrumentation platform. Each pixel emits events throughout the day; some events are missing (not observed) and some...

Data Manipulation (SQL/Python)
0
1
11 people solved
Aug 1, 2025
Meta logo
Meta
Medium
Data Engineer

Design visualizations for streaming metrics

Design visualizations for streaming metrics Design a Monitoring and Diagnosis Visualization for a Video-Streaming Metric Context You are building an o...

Analytics & Experimentation
6
0
47 people solved
Aug 1, 2025
Meta logo
Meta
Medium
Data Engineer

Recommend two-hop follows in Python

Given a directed "follows" graph as a Python dict[str, list[str]], implement recommend_two_hop(graph, user) that returns the set (or a sorted list) of...

Data Manipulation (SQL/Python)
3
0
31 people solved
Aug 1, 2025
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Meta
Medium
Machine Learning Engineer

Check diagonal equality in a matrix

Given an m x n integer matrix, determine whether every top-left to bottom-right diagonal contains identical values (all elements along each such diago...

Coding & Algorithms
6
0
62 people solved
Jul 31, 2025
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Meta
Medium
Machine Learning Engineer

Implement sliding-window moving average

Design a class MovingAverage that supports a constructor MovingAverage(k) and a method next(val) returning the average of the last k values from a dat...

Coding & Algorithms
5
2
44 people solved
Jul 31, 2025
Meta logo
Meta
Medium
Software Engineer

Solve three LeetCode coding problems

Question LeetCode 1249. Minimum Remove to Make Valid Parentheses LeetCode 827. Making A Large Island LeetCode 199. Binary Tree Right Side View https:/...

Coding & Algorithms
8
0
24 people solved
Jul 29, 2025
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Meta
Medium
Software Engineer

Compare two string linked lists

Question Given two singly linked lists where each node stores one character as a string, determine whether the sequences of characters represented by ...

Coding & Algorithms
7
0
20 people solved
Jul 29, 2025
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Meta
Medium
Software Engineer

Solve LeetCode array & stream problems

Question LeetCode 346. Moving Average from Data Stream LeetCode 249. Group Shifted Strings LeetCode 163. Missing Ranges Remove duplicates from a chara...

Coding & Algorithms
19
0
60 people solved
Jul 29, 2025
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Meta
Medium
Software Engineer

Check tree nodes equal subtree average

Question LeetCode 2265. Count Nodes Equal to Average of Subtree – Adapted: Verify that every node’s value equals the average of all values in its subt...

Coding & Algorithms
12
0
29 people solved
Jul 29, 2025
Meta logo
Meta
Medium
Software Engineer

Find closest BST value and remove parentheses

Question LeetCode 270. Closest Binary Search Tree Value LeetCode 1249. Minimum Remove to Make Valid Parentheses (follow-up: achieve without using a st...

Coding & Algorithms
13
0
55 people solved
Jul 29, 2025
Meta logo
Meta
Medium
Software Engineer

Solve tree leaf sum and target indices search

Question LeetCode 129. Sum Root to Leaf Numbers LeetCode 2089. Find Target Indices After Sorting Array (array already sorted; require O(log n) time) h...

Coding & Algorithms
7
0
34 people solved
Jul 29, 2025
Meta logo
Meta
Medium
Software Engineer

Find integer in most intervals

Question Given N integer intervals [ai, bi] (positive integers), find an integer that belongs to the maximum number of intervals (return any such inte...

Coding & Algorithms
7
0
18 people solved
Jul 29, 2025
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Meta
Medium
Software Engineer

Solve classic LeetCode problems

Question LeetCode 215. Kth Largest Element in an Array LeetCode 249. Group Shifted Strings Variant of LeetCode 56. Merge Intervals extended to 2-D rec...

Coding & Algorithms
7
0
34 people solved
Jul 29, 2025
Meta logo
Meta
Medium
Software Engineer

Handle palindrome & decimal addition

Question LeetCode 266. Palindrome Permutation Given two non-negative decimal number strings, implement addition that supports a decimal point. https:/...

Coding & Algorithms
11
0
35 people solved
Jul 29, 2025
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Meta
Medium
Software Engineer

Solve 4 LeetCode algorithm problems

Question LeetCode 636. Exclusive Time of Functions LeetCode 253. Meeting Rooms II LeetCode 314. Binary Tree Vertical Order Traversal LeetCode 215. Kth...

Coding & Algorithms
1
0
7 people solved
Jul 29, 2025
Meta logo
Meta
Medium
Software Engineer

Solve various LeetCode data-structure questions

Question LeetCode 129. Sum Root to Leaf Numbers LeetCode 2089. Find Target Indices After Sorting Array LeetCode 270. Closest Binary Search Tree Value ...

Coding & Algorithms
16
0
46 people solved
Jul 29, 2025

Frequently Asked Questions

How difficult are Meta interview questions?
Meta interview questions span a wide difficulty range because they must screen candidates from entry to senior levels across many functions. Expect coding rounds to map to medium-to-hard algorithmic problems that appear in top 100 problem lists for software engineers, and expect data roles to face challenging SQL, experiment diagnosis, and product-analytics problems that require clean metric definitions. Machine learning roles emphasize recommendation and ranking tradeoffs and model complexity, while data engineers encounter large-scale ETL and modeling puzzles. Difficulty scales with level: entry hires see clearer, bounded problems; senior hires face ambiguous tradeoffs and system-wide thinking.
What is Meta's interview process and where do these questions appear?
Meta typically runs a multi-stage process: recruiter screen, one or two technical screens or an online assessment, a full loop of onsite-style interviews, then debrief, committee review, and offer. The full loop mixes coding, system or product design, role-specific technical rounds, and behavioral interviews. Software-engineer candidates spend most time on coding and design; data scientists focus on SQL, experimentation, and product analytics; machine-learning engineers see modeling and recommendation design; data engineers handle SQL, data modeling, and pipeline questions; PMs get product-design and analytics probes. In 2025–2026 some teams pilot AI-enabled coding rounds.
How should I structure a preparation timeline for a Meta interview?
A focused six-week plan works well: weeks one and two cover fundamentals—data structures, algorithms, SQL basics, and experiment design; weeks three and four emphasize timed problem practice, mock phone screens, and role-specific cases (A/B diagnosis for data scientists, model design for MLEs, ETL modeling for data engineers); week five concentrates on system or product design and behavioral storytelling; week six is for full mock loops, timing, and refining communication. Practice with realistic tools, simulate loop pacing, and schedule a debrief after each mock to iterate on clarity, edge-case handling, and time management.
Which technical subtopics are most commonly tested for each role at Meta?
For Data Scientist interviews the recurring technical themes are product-metric definition, diagnosing experiment and spend drops, counting multi-account interactions, SQL for multi-entity metrics, and ranking or recommendation evaluation such as shop ad ranking. Software-engineer questions frequently focus on timestamped state and versioned systems, leaderboards and ranking, maze/graph traversal and tree/array transforms, delimiter and CSV parsing, and scalable search or flight-search style designs. Machine-learning engineers see place and friend recommendation design, sparse-matrix operations, ranking/loss choices, and feed dislike or personalization models. Data engineers repeatedly face entity modeling for feed and booking data, SQL analytics for utilization and reservations, and capacity-aware aggregation challenges.
What standout tips and common pitfalls should I watch for in Meta interviews?
Start interviews by clarifying requirements and expected outputs, then propose measurable success metrics; this prevents misaligned solutions. For coding, think aloud, handle edge cases, state complexity up front, and write a couple of quick tests. In design rounds quantify load, storage, and tradeoffs rather than vague features. Data roles must define metrics, guardrails, and experiment assumptions before jumping to analysis; common pitfalls are ambiguous metric definitions, peeking at tests, and ignoring instrumentation limits. For AI-assisted coding rounds, use the assistant to accelerate boilerplate but validate logic and corner cases yourself. Finish each answer with a concise summary of impact and tradeoffs.

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