Meta Interview Questions

Meta Behavioral & Leadership Interview Questions

Practice 1,166 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 Company08.08.2026
Showing 20 results
Role
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Meta
Medium
Data Engineer

Define success metrics for a social feed

Define Success Metrics for a Social Feed Feature You are evaluating a change to the main social feed in a large-scale consumer app. Assume events are ...

Analytics & Experimentation
8
0
70 people solved
Sep 6, 2025
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Meta
Hard
Machine Learning Engineer

Design scalable media storage and delivery

System Design: Global UGC Photos and Short Videos Store/Delivery Context Design a globally distributed system to store and deliver user-generated phot...

System Design
7
0
52 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer Locked

Design a fitness tracking app

This question evaluates a candidate's competency in designing end-to-end backend architectures, specifying core APIs, modeling workout and geospatial ...

System Design
7
0
61 people solved
Mar 12, 2026
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Meta
Medium
Software Engineer AI Locked

Solve array, tree, and maze problems

This question evaluates algorithmic problem-solving across arrays, binary trees, and grid pathfinding, testing competencies in array traversal and vis...

Coding & Algorithms
5
0
54 people solved
Mar 12, 2026
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Meta
Medium
Data Scientist

Describe a high-impact product project

In a conversation with a Head of Product, you are asked to discuss one project in depth. Describe a product or marketplace project where you had meani...

Behavioral & Leadership
6
0
75 people solved
Mar 11, 2026
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Meta
Medium
Machine Learning Engineer Locked

Design concurrent expiring job registry

This question evaluates understanding of concurrent data structures, synchronization primitives, time-based expiration semantics, and efficient cleanu...

Software Engineering Fundamentals
2
0
29 people solved
Nov 28, 2025
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Meta
Medium
Machine Learning Engineer Locked

Build harmful-content text classifier

This question evaluates a candidate's competence in designing an end-to-end machine learning pipeline for binary text classification, covering data un...

Machine Learning
7
0
54 people solved
Nov 28, 2025
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Meta
Hard
Software EngineerSenior+

Describe conflict resolution and mentoring experiences

You are interviewing for an engineering manager or senior engineer role. Prepare structured behavioral answers for these four prompts: 1. Describe a s...

Behavioral & Leadership
4
0
40 people solved
Mar 23, 2025
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Meta
Hard
Data Scientist

Compute High-Call Usage Rates

You are given two tables for a voice-calling product: users - user_id BIGINT - country_code STRING calls - call_id BIGINT - caller_id BIGINT - recipie...

Data Manipulation (SQL/Python)
3
0
30 people solved
Mar 4, 2026
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Meta
Medium
Software Engineer

Design a Scalable Post, Feed, and Search Service

Design a Scalable Post, Feed, and Search Service Design a social-post service with three core capabilities: a user can publish a text post, retrieve a...

System Design
1
0
11 people solved
Mar 2, 2026
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Meta
Medium
Data Scientist Locked

Evaluate AI-assisted ad creation

This question evaluates a candidate's competence in product analytics, causal inference, experimentation design, metric definition, and monitoring for...

Analytics & Experimentation
5
0
75 people solved
Mar 1, 2026
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Meta
Hard
Software Engineer Locked

Guide a mouse to find cheese with APIs

This question evaluates the ability to reason about graph exploration and stateful API interaction in an unknown 2D grid, assessing competencies in se...

Coding & Algorithms
3
0
47 people solved
Nov 12, 2025
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Meta
Medium
Machine Learning Engineer Locked

Solve Merge Lists and Vertical Traversal

This question evaluates proficiency with merging sorted linked lists and performing vertical traversal of binary trees, focusing on algorithms, data s...

Coding & Algorithms
7
0
52 people solved
Feb 28, 2026
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Meta
Medium
Data Scientist

What features and feature selection would you use?

Context You are building an ML system to rank/promote shop ads in an e-commerce feed/search page. At serving time, the system may score candidate shop...

Machine Learning
3
0
32 people solved
Aug 10, 2025
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Meta
Easy
Machine Learning EngineerSenior+ Locked

Solve Tree Views, Columns, and Calculator

This multi-part question evaluates skills in binary tree traversal and view extraction, vertical column grouping and ordering of tree nodes, and parsi...

Coding & Algorithms
3
0
35 people solved
Feb 27, 2026
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Meta
Medium
Software Engineer

Group a tree by vertical columns

Group a tree by vertical columns Given the root of a binary tree, produce a vertical listing of nodes: assign each node an x-coordinate (root at x=0; ...

Coding & Algorithms
2
0
32 people solved
Aug 7, 2025
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Meta
Hard
Software Engineer

Design an online auction system

Design an online auction system System Design: Real-Time Online Auction Platform You are asked to design an online auction system that supports real-t...

System Design
6
0
55 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Design an online chess platform

Design an online chess platform. Requirements: - User matchmaking (ranked/unranked). - Real-time gameplay with low latency moves. - Enforce game rules...

System Design
6
0
54 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Design a YouTube/Netflix video platform

Design a video platform similar to YouTube/Netflix. Requirements: - Upload videos (for YouTube-like) and/or ingest catalog (for Netflix-like). - Trans...

System Design
3
0
65 people solved
Feb 25, 2026
Meta logo
Meta
Medium
Software Engineer

Design a chat messaging system

Design a chat system similar to WhatsApp/Messenger. Requirements: - 1:1 and group chats. - Send/receive messages in real time when online; store-and-f...

System Design
6
0
44 people solved
Feb 25, 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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