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
Software Engineer

Describe an ambiguous project you handled

Describe a time when you worked on a project with a lot of ambiguity (unclear requirements, unknown constraints, or shifting priorities). Explain: - W...

Behavioral & Leadership
2
0
48 people solved
Dec 8, 2025
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Meta
Medium
Software Engineer

Describe a failed project and lessons learned

Describe a project you worked on that ultimately failed or did not meet its goals. Explain: - What the project was trying to achieve and your role. - ...

Behavioral & Leadership
2
0
39 people solved
Dec 8, 2025
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Meta
Medium
Software Engineer

Design an online coding platform

Design an online coding practice and interview platform (similar to well-known coding challenge sites). The platform should allow: - Users to sign up,...

System Design
5
0
45 people solved
Dec 8, 2025
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Meta
Medium
Product Manager

Hiking App: Design, Metrics, and Go-to-Market

Hiking App: Design, Metrics, and Go-to-Market You are a Product Manager asked to design a consumer hiking mobile app from zero. Assume iOS and Android...

Product / Decision Making
16
0
67 people solved
Jul 4, 2025
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Meta
Medium
Product Manager

Core Behavioral Reflections

Core Behavioral Reflections for Product Managers Prepare concise, structured responses for four Product Manager behavioral prompts: professional failu...

Behavioral & Leadership
9
0
57 people solved
Jul 4, 2025
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Meta
Medium
Product Manager

Program Execution Deep Dive

Program Execution Deep Dive Describe an end-to-end program or product you led as a Product Manager. The interviewer wants to understand how you captur...

Product / Decision Making
10
0
60 people solved
Jul 4, 2025
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Meta
Medium
Product Manager

Dog-Walking Marketplace & Architecture

Design a Dog-Walking Marketplace App Design a two-sided marketplace that connects dog owners who need walks with vetted dog walkers who provide them. ...

Product / Decision Making
4
0
42 people solved
Jul 4, 2025
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Meta
Medium
Product Manager

Children’s Bookshelf Product Design

Product Design Prompt: Children's Bookshelf Design a primarily physical bookshelf for children to use at home, with optional lightweight digital suppo...

Product / Decision Making
12
0
44 people solved
Jul 4, 2025
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Meta
Medium
Software Engineer

Design a Coding Contest Platform

Design an online coding contest platform that supports programming competitions, code submission, automated judging, and live leaderboards. The platfo...

System Design
1
0
23 people solved
Mar 17, 2026
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Meta
Medium
Software Engineer AI

Maximize Unique Characters from Words

You are given a list of lowercase English words. Select a subset of the words such that no character appears more than once across all selected words....

Coding & Algorithms
1
0
13 people solved
Mar 17, 2026
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Meta
Medium
Software Engineer

Explain key ML metrics and techniques

You are asked a set of short conceptual machine learning questions. 1. Confusion matrix and metrics For a binary classification problem: - Def...

Machine Learning
7
0
68 people solved
Dec 8, 2025
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Meta
Medium
Data Scientist Locked

Write SQL for multi-account metrics

This question evaluates proficiency in SQL for multi-table aggregation, grouping, joins, and conditional counting within a user-account-notification s...

Data Manipulation (SQL/Python)
7
1
52 people solved
Mar 16, 2026
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Meta
Easy
Data Scientist

Describe a challenging project and work-style conflicts

Question This is the Meta Data Scientist onsite behavioral & leadership round. The anchor prompt is to describe your most challenging recent project e...

Behavioral & Leadership
16
0
101 people solved
Dec 6, 2025
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Meta
Medium
Data Scientist Locked

Assess Demand for Group Video Chat

This question evaluates skills in product analytics, causal inference from observational data, demand estimation, survey design, and executive-level s...

Analytics & Experimentation
7
0
78 people solved
Mar 14, 2026
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Meta
Easy
Data Scientist

Compute maximum score using up to 3 categories

Problem A library runs a summer reading program. Each book a student reads earns a certain number of points, and each book belongs to a category. A st...

Coding & Algorithms
5
0
72 people solved
Dec 2, 2025
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Meta
Hard
Machine Learning Engineer

Design nearby place recommendations

Real‑Time Nearby Places Recommendation System Context Design a mobile feature that recommends nearby places (e.g., restaurants, shops, attractions) to...

ML System Design
9
1
118 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Walk through resume and plan team success

Behavioral/Leadership Prompt — Technical Screen (Software Engineer) You are interviewing for a Software Engineer role in a technical screen focused on...

Behavioral & Leadership
4
0
40 people solved
Sep 6, 2025
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Meta
Medium
Data Engineer

Define and analyze product metrics

Product Analytics Case: Short‑Form Video Feed Context: You are evaluating a short‑form video feed feature inside a large social app where users swipe ...

Analytics & Experimentation
9
1
63 people solved
Sep 6, 2025
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Meta
Hard
Software Engineer

Design an Instagram-like photo-sharing platform

System Design: Instagram-like Photo and Short-Video Platform Goal Design an Instagram-like platform for photos and short videos. The design should cov...

System Design
4
0
47 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Find mode or minimum with time-space tradeoffs

For an unsorted array of integers, implement two functions: ( 1) return the minimum value; ( 2) return the value that appears most frequently (the mod...

Coding & Algorithms
5
0
38 people solved
Sep 6, 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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