Prepare for your Meta software engineering interview

Algorithms, system design, and behavioral rounds calibrated to Meta's rigorous coding culture, social graph scale, and move-fast engineering philosophy.

Socratify AI

The Interview

What Meta is looking for

Coding Interview

Algorithm & Data Structures

01Pattern Recognition & Speed

02Optimization Trade-offs

03Edge Case Handling

04Code Quality & Clarity

System Design Interview

Social Scale Architecture

01Social Graph & Feed Systems

02Content Distribution at 3B+ Scale

03Real-Time Messaging & Notifications

04Privacy & Data Architecture

Behavioral Interview

01Move Fast & Ship

02Impact & Ownership

03Cross-Functional Influence

04Learning from Failures

Rigorous multi-round coding at speed and depth//Social graph systems design at 3B+ user scale//Move fast, ship, and own impact culture

Practice Library

Meta exercises

Ready to ace your Meta software engineering interview?

Prepare for your Meta software engineering interview

Algorithms, system design, and behavioral rounds calibrated to Meta's rigorous coding culture, social graph scale, and move-fast engineering philosophy.

Socratify AI

The Interview

What Meta is looking for

Coding Interview

Algorithm & Data Structures

01Pattern Recognition & Speed

02Optimization Trade-offs

03Edge Case Handling

04Code Quality & Clarity

System Design Interview

Social Scale Architecture

01Social Graph & Feed Systems

02Content Distribution at 3B+ Scale

03Real-Time Messaging & Notifications

04Privacy & Data Architecture

Behavioral Interview

01Move Fast & Ship

02Impact & Ownership

03Cross-Functional Influence

04Learning from Failures

Rigorous multi-round coding at speed and depth//Social graph systems design at 3B+ user scale//Move fast, ship, and own impact culture

How It Works

Master Meta Software Engineering Interviews

Coding, system design, and behavioral rounds scored on Meta's engineering fundamentals, social scale, and impact-ownership evaluation dimensions. · Click to expand

System Design

Practitioner

Algorithm Design

Practitioner

1Your Software Goals

2Software Case Prep

Implement the word break problem: given a string and dictionary, determine if it can be...

LEARNMedium

Technology · Dynamic ProgrammingMeta

3Frameworks

Framework

Is the query execution path the primary bottleneck?

Is the ranking model adding disproportionate computation time?

Feature computation for 500 results: 620ms avg — 73% of P99 budget consumed by ranking alone

Top-3 features use O(n²) cross-product — 500 results × 500 dimensions = 250K ops per query

Is the index scan missing an optimal access path?

Query plan: full table scan on filtered dimension — composite index missing on (category, score)

Adding composite index reduces scan from 2M rows to 1.2K rows — 1,600× selectivity improvement

Is network and serialization overhead contributing significantly?

Is the response payload larger than the client actually needs?

Response: 2.3MB uncompressed for 500 results — 97% of fields unused by frontend client

Field projection reduces payload to 48KB — 98% reduction, 140ms serialization saving per request

Is JSON serialization blocking the response thread?

Serialization on main thread: 85ms measured — async streaming available but not enabled

P50 latency drops 70ms after async serialization migration — thread blocking confirmed

Is the caching strategy ineffective for this query workload?

Is the cache hit rate too low for the observed query distribution?

Cache hit rate: 23% (target 70%) — LRU eviction removing hot items due to 10K-item tail queries

Top 200 query patterns account for 78% of traffic — LFU cache would raise hit rate to 68%

Is cache invalidation too aggressive, causing unnecessary misses?

TTL: 30s global — stable brand-name queries invalidated 120×/hour despite no underlying data change

Tiered TTL (stable: 10 min, dynamic: 30s) reduces invalidation events 85% with <0.1% staleness

Complexity Analysis

Distinctive

Distributed Systems

Strong

Technical Communication

Meeting Bar

Pragmatic Trade-offs

Strong

4Feedback

How It Works

Master Meta Software Engineering Interviews

Coding, system design, and behavioral rounds scored on Meta's engineering fundamentals, social scale, and impact-ownership evaluation dimensions. · Click to expand

1Your Software Goals

System Design

Practitioner

Algorithm Design

Practitioner

2Software Case Prep

Implement the word break problem: given a string and dictionary, determine if it can be...

LEARNMedium

Meta exercises

Implement a function to find the word break problem: given a string and a word...

LEARNMedium

Technology · Dynamic ProgrammingMeta

Design Meta's News Feed system for 3B+ users. Cover feed generation, ranking,...

CASE INTERVIEWHard

Social Media · System DesignMeta

Given a stream of integers, find the k most frequent elements. Optimize for memory and...

CASE INTERVIEWHard

Technology · Heap / Hash MapMeta

Describe a time when you had to optimize a system or algorithm for production scale...

BEHAVIORALMedium

Behavioral · Optimization & ScaleMeta

Tell me about a complex technical decision you owned end-to-end. How did you drive...

BEHAVIORALMedium

Behavioral · Ownership & ImpactMeta