AI Engineering Interview Prep
Everything asked in AI/ML engineering interviews at top companies. Coding, system design, and ML theory.
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Video1 hr 20 minAndrej Karpathy — How LLMs Work
The definitive explanation of how large language models work, by the former Director of AI at Tesla.
Open resource- Article25 min read
System Design for ML — Chip Huyen
How to answer ML system design questions. Common patterns and tradeoffs.
Open resource - Article20 min read
Top AI/ML Interview Questions 2025
Curated ML interview questions from Google, Amazon, Microsoft with sample answers.
Open resource 
Video2 hrRAG from Scratch — LangChain
Build a RAG system from scratch. Commonly asked in AI engineering technical interviews.
Open resource- Paper30 min read
Attention Is All You Need — Paper
The transformer paper. Interviewers often ask you to explain attention mechanisms.
Open resource - Article30 min
LeetCode - ML / DS interview patterns
Practice coding patterns that show up in AI SWE loops.
Open resource - Article45 min
Stanford CS229 - ML course materials
Foundations interviewers expect for classical ML fluency.
Open resource 
Video40 minDeepLearning.AI - LangChain for LLM apps
Chains, agents, and memory — common live-coding topics.
Open resource- Article35 min
System design primer - distributed systems
Latency, caching, and scaling vocabulary for ML services.
Open resource - Docs20 min
Papers with Code - SOTA leaderboards
How to discuss benchmarks and model families credibly.
Open resource - Docs25 min
AWS - ML interview preparation
Cloud patterns for training and inference at scale.
Open resource - Article30 min
NeurIPS - Ethics & safety reading list
Discussing fairness, robustness, and deployment risk.
Open resource 
Video50 minGoogle ML crash course - TensorFlow
Quick refresh on graphs, loss, and evaluation metrics.
Open resource- Article40 min
Kaggle - Feature engineering micro-courses
Tabular ML intuition still appears in hybrid AI roles.
Open resource - Docs28 min
Meta PyTorch - Performance tuning
GPU utilization and batching talking points for infra rounds.
Open resource
