ML System Design: Build a Fraud Detection System
Fraud detection is one of the highest-stakes ML applications — a false negative costs money, a false positive costs a […]
AI/ML Interview Questions
AI/ML Interview Questions
ML System Design: Build a Spam Classifier
“Design a spam classifier” is one of the most common ML system design questions at Google, Meta, and Microsoft. Unlike
AI/ML Interview Questions
How to Detect Model Drift in Production
Model drift is one of the most common production ML failure modes — and one of the most underestimated in
AI/ML Interview Questions
NLP Interview Questions: Tokenization, Embeddings, and BERT
NLP interview questions appear across ML engineer, data scientist, and applied researcher roles at companies like Google, Meta, OpenAI, and
AI/ML Interview Questions
Computer Vision Interview Questions: CNNs, Object Detection, and Transfer Learning
Computer vision is one of the most interview-tested areas of ML, especially at companies with physical products, autonomous systems, or
AI/ML Interview Questions
How Does RLHF Work? Reinforcement Learning from Human Feedback Explained
RLHF (Reinforcement Learning from Human Feedback) is the technique that transforms a raw language model into an assistant — the
System Design
Design an LLM Inference API
Design an LLM inference API — the service that accepts user prompts and returns model completions, like the OpenAI API,
System Design
Design a Recommendation Engine (Netflix-style)
Design a recommendation engine like Netflix’s, Spotify’s Discover Weekly, or Amazon’s “Customers also bought.” Recommendation systems are one of the
System Design
Design Google Docs: Collaborative Editing and CRDTs
Design a real-time collaborative document editor like Google Docs. This is one of the most technically nuanced system design problems
AI/ML Interview Questions
Embeddings and Vector Databases Explained
Embeddings are the lingua franca of modern AI applications. They power semantic search, RAG, recommendation systems, duplicate detection, and anomaly
AI/ML Interview Questions
What is RAG? Retrieval-Augmented Generation vs Fine-tuning
Retrieval-Augmented Generation (RAG) is one of the most widely deployed LLM patterns in production. Understanding when to use RAG versus
System Design
Design an Ad Click Aggregation System
Design an ad click aggregation system — the infrastructure that counts how many times each ad was clicked, detects fraud,
System Design
Design a Monitoring and Alerting System
Design a monitoring and alerting system like Datadog, Prometheus + Grafana, or New Relic. This is a system design problem
AI/ML Interview Questions
Fine-tuning LLMs vs Training from Scratch: When and How
One of the most common LLM interview questions in 2026: “Would you fine-tune a model or train from scratch?” Almost
AI/ML Interview Questions
How Transformer Models Work: Attention Mechanism Explained
Transformers are the architecture behind GPT, BERT, Claude, and every other major language model. Understanding how they work — especially