FAANG interview prep 15 questions 30 min

Google FAANG MCQ · test your interview readiness

Machine learning, system design, coding patterns, and behavioral insights – 15 questions inspired by big tech interviews.

Easy: 5 Medium: 6 Hard: 4
ML basics
System design
Coding patterns
Behavioral

Cracking the FAANG interview: core pillars

FAANG (Facebook/Meta, Amazon, Apple, Netflix, Google) interviews typically test four areas: coding & algorithms, system design, machine learning (for AI roles), and behavioral fit. This MCQ covers fundamental concepts you're likely to encounter, from ML basics to design tradeoffs.

The FAANG mindset

Interviewers look for structured thinking, clarity, and depth. Even MCQ answers require understanding why an option is correct – not just memorization.

Interview glossary – key concepts

System design

High‑level architecture: load balancing, caching, databases, microservices, CAP theorem.

Algorithm patterns

Two pointers, sliding window, BFS/DFS, dynamic programming, union‑find.

ML basics

Bias‑variance tradeoff, overfitting, regularization, gradient descent, evaluation metrics.

Data engineering

ETL, data warehousing, Spark, MapReduce, consistency models.

Behavioral (STAR)

Situation, Task, Action, Result – structured way to answer experience questions.

Tradeoffs

Consistency vs availability (CAP), read‑vs write‑optimization, latency vs throughput.

# Common Python interview snippet: LRU cache (O(1) get/put)
from collections import OrderedDict
class LRUCache:
    def __init__(self, capacity):
        self.cache = OrderedDict()
        self.cap = capacity
    def get(self, key):
        if key not in self.cache: return -1
        self.cache.move_to_end(key)
        return self.cache[key]
    def put(self, key, value):
        if key in self.cache:
            self.cache.move_to_end(key)
        self.cache[key] = value
        if len(self.cache) > self.cap:
            self.cache.popitem(last=False)
Interview tip: For any MCQ, first eliminate obviously wrong answers. Then reason about the remaining options using first principles. After the quiz, review explanations to fill knowledge gaps.

Common FAANG interview themes

  • Explain the CAP theorem and when you'd choose AP over CP.
  • Design a URL shortening service (like bit.ly).
  • What is the bias‑variance tradeoff? How do you diagnose high bias?
  • Implement a thread‑safe singleton in Python.
  • Tell me about a time you had to influence without authority (behavioral).
  • How would you detect anomalies in real‑time metrics?
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