Skill-based interview questions

Python

Data structures, mutability, comprehensions, and common interview gotchas.

OOP

Classes, inheritance, polymorphism, encapsulation, and design questions.

DSA

Arrays, trees, graphs, complexity analysis, and classic coding problems.

Git & GitHub

Branching, merging, rebasing, and everyday version control questions.

Linear Algebra

Vectors, matrices, eigenvalues, and the math behind ML models.

Calculus

Derivatives, gradients, chain rule, and the math behind backprop.

Probability

Bayes' theorem, distributions, expectation, and probabilistic reasoning.

Statistics

Hypothesis testing, confidence intervals, A/B testing, and inference.

SQL

Joins, aggregations, window functions, and query-writing problems.

DBMS

Transactions, indexing, normalization, and database design tradeoffs.

FastAPI

Routing, dependency injection, async endpoints, and API design.

Machine Learning

Model evaluation, bias-variance, feature engineering, and ML systems.

Deep Learning

Backprop, activations, CNNs, transformers, and training behavior.

NLP

Tokenization, embeddings, and text representation questions.

LLMs

Context windows, prompting, fine-tuning, and LLM deployment.

Prompt Engineering

Prompt design, few-shot examples, and structured output reliability.

RAG

Chunking, retrieval, reranking, and grounded generation pipelines.

AI Agents

Tool use, planning, memory, and agent reliability questions.

MCP

Hosts, clients, servers, and model-to-tool connection standards.

Docker

Images, containers, networking, and containerization workflows.

Kubernetes

Pods, deployments, scaling, and orchestration questions.

MLOps

Pipelines, experiment tracking, model serving, and monitoring.

System Design for AI

Architecture, latency, cost, and scaling tradeoffs for AI systems.

Case Study

Open-ended business and product case questions for technical roles.