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
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Meta
Medium
Data Scientist

Leverage Data Sources for Effective Push Notification Strategy

Data Sources and Metrics for Push Notification Strategy A product team wants to improve the quality and impact of mobile push notifications for a cons...

Analytics & Experimentation
8
0
36 people solved
Jul 12, 2025
Meta logo
Meta
Hard
Product Manager

Product Metrics & Debugging Scenarios

Product Metrics and Debugging Scenarios You are a PM candidate evaluating data, metrics, and operational plans for large-scale consumer products. Answ...

Product / Decision Making
11
0
52 people solved
Jul 4, 2025
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Meta
Hard
Product Manager

Design Parking for Google Maps

Design a parking-finding experience for Google Maps. Assume the product goal is to help drivers reduce uncertainty and wasted time when parking near a...

Product Design & Strategy
4
0
32 people solved
Feb 22, 2024
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Meta
Hard
Product Manager

Define Meta Pay Success

Meta Pay is a payments product used across Meta's ecosystem. Define how you would determine whether Meta Pay is successful, then make a product priori...

Product / Decision Making
3
0
29 people solved
Feb 22, 2024
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Meta
Medium
Software EngineerSenior+

Choose the Cheapest Round Trip

Choose the Cheapest Round Trip You are given two arrays of equal length. departure[i] is the cost of departing on day i, and return_cost[j] is the cos...

Coding & Algorithms
1
1
17 people solved
Jul 6, 2026
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Meta
Hard
Machine Learning Engineer Locked

Simulate Monster Team Battles

This question evaluates a candidate's ability to model stateful simulations and implement deterministic battle mechanics with clean data structures an...

Coding & Algorithms
1
0
20 people solved
May 19, 2026
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Meta
Medium
Software Engineer AI Locked

Solve a Key-Door Corridor Maze

This question evaluates graph search and state-space reasoning by requiring shortest-path computation in a constrained one-dimensional maze with colle...

Coding & Algorithms
2
0
33 people solved
May 14, 2026
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Meta
Medium
Data Scientist

Compute ad impression conversion rates

You are given two tables for an ads product. Table: ad_impressions | Column | Type | Description | |---|---:|---| | impression_id | STRING | Unique id...

Data Manipulation (SQL/Python)
1
0
12 people solved
Apr 30, 2026
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Meta
Medium
Software Engineer

Solve Array Merge and Parentheses Cleanup

You are asked to solve two coding problems. Problem 1: Merge Three Sorted Arrays Given three integer arrays, each sorted in nondecreasing order, merge...

Coding & Algorithms
1
0
13 people solved
Apr 29, 2026
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Meta
Hard
Software Engineer AI

Solve Two Backtracking Array Problems

You will solve two independent coding problems. For each problem, first discuss edge cases, then implement a correct solution, and finally explain how...

Coding & Algorithms
36
0
291 people solved
Apr 27, 2026
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Meta
Easy
Software Engineer

Solve Tree View and Triplet Sum

You are asked to solve two coding problems. Problem 1: Return the nodes visible from the right Given the root of a binary tree, return the values of t...

Coding & Algorithms
0
0
10 people solved
Apr 24, 2026
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Meta
Medium
Software Engineer

Solve Array, Matrix, and Recommendation Problems

During an onsite coding interview, solve the following independent tasks. Problem 1: In-place unique prefix You are given a nondecreasing integer arra...

Coding & Algorithms
0
0
16 people solved
Apr 17, 2026
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Meta
Medium
Machine Learning Engineer AI

Find a String Containing Another

Given a list of strings, determine whether any string in the list contains another string from the same list as a contiguous substring. Return one str...

Coding & Algorithms
0
0
14 people solved
Apr 16, 2026
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Meta
Hard
Software EngineerSenior+

Solve Subarray Sum and Local Minimum

Two coding problems were reported in the same phone-screen round: 1. Count target-sum subarrays. Given an integer array nums and an integer k, return ...

Coding & Algorithms
5
0
39 people solved
Apr 15, 2026
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Meta
Medium
Backend Engineer AI Locked

Solve coding and AI-assisted tasks

This set evaluates algorithmic problem-solving across arrays, immutable linked-list interfaces, parent-pointer tree traversal, string validity via min...

Coding & Algorithms
8
0
65 people solved
Apr 8, 2026
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Meta
Medium
Software EngineerSenior+ AI

Infer an Unknown Alphabet Order

You are given a list of words that is already sorted according to an unknown alphabet. Derive one valid ordering of the characters in that alphabet. R...

Coding & Algorithms
1
0
20 people solved
Apr 8, 2026
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Meta
Medium
Software Engineer AI

Implement an Expiring Record Store

Implement a level-based in-memory record store. The store contains records identified by a string key. Each record contains fields, where each field i...

Coding & Algorithms
2
0
30 people solved
Apr 1, 2026
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Meta
Easy
Software Engineer Locked

Implement array parity and tree level views

This question evaluates proficiency in array frequency analysis and binary tree traversal, testing skills in data structures, correctness reasoning, a...

Coding & Algorithms
5
0
38 people solved
Mar 24, 2026
Meta logo
Meta
Medium
Data Scientist Locked

Count heavy callers in 7 days

This question evaluates proficiency in SQL-based data manipulation and analytics, covering joins between user and call records, aggregation and distin...

Data Manipulation (SQL/Python)
7
0
66 people solved
Mar 24, 2026
Meta logo
Meta
Medium
Software Engineer

Solve Four Online Assessment Problems

Complete the following four independent coding tasks. For each task, write a function that returns the requested result. 1. Find the best value index ...

Coding & Algorithms
10
0
84 people solved
Mar 19, 2026

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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