Crack ML/GenAI Interviews in 2025

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MLUME gives you a complete learning roadmap from fundamentals to production-grade AI systems – designed by experts, trusted by learners.

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What You’ll Learn on MLUME

A complete roadmap from foundational ML concepts to production-grade GenAI systems.

Math Foundations
Linear algebra, probability, calculus, and stats for ML/LLMs.
 Algorithms & Data
Core data structures, algorithms, and advanced SQL for data manipulation.
 Machine Learning
Model types, training, evaluation, tuning, and deployment basics.
 Deep Learning
NNs, CNNs, Transformers, Backpropagation, and key architectures.
 GenAI & LLMs
Transformers, fine-tuning, embeddings, RAG, LangChain, and OpenAI API.
 ML System Design
End-to-end pipeline design, MLOps, model serving, and scalability.



Why MLUME?

  • ✅ Interview-Focused: Content tailored for ML, GenAI, and LLM roles.
  • 🧠 Deep Intuition: Visual explanations connecting math, code, and core ideas.
  • 🛠️ Modern Toolkit: Hands-on guides for RAG, LangChain, HuggingFace, and more.
  • 📈 Data Mastery: Advanced SQL, analytics, and real-world data case studies.
  • 💼 Product Sense: Case study walk-throughs to build business and product intuition.
  • 🔍 Expert-Curated: Developed and vetted by active ML researchers and engineers.
MLUME Product



Engineered for the Modern AI Interview

6 Core Interview Pillars

From Math and Coding fundamentals to advanced LLMs and System Design, we cover every angle of the modern AI interview.

360° Learning Framework

Each topic is broken down into Roadmaps, Cheatsheets, Math, Code, and System Design to build deep, interview-ready knowledge.

Focused on 2025 Interviews

Our content is relentlessly updated to cover the latest trends you'll be asked about, including RAG, AI Agents, and Multimodal Models.



The Anatomy of Interview Success

Every AI & ML topic is meticulously broken down into six core components, giving you the deep, structured knowledge that top companies demand.

Roadmaps

Step-by-step learning paths.

Cheatsheets

Quick-reference summaries.

Comparisons

Pros vs. Cons analysis.

Coding

Practical implementations.

Math

Core intuition and theory.

System Design

Scalable ML architecture.



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Frequently Asked Questions

🔍 Where does MLUME collect AI questions from?
  • All content are created manually by us for educational purposes only.
  • We do not claim affiliation with any company.
💡 Are the questions updated regularly?
  • Yes - the question bank is updated every month.
📘 Is MLUME suitable for beginners?
  • Absolutely. Our content is designed in layers - covering core concepts.
🧪 Do you cover research or system design roles too?
  • Yes. We include Research Scientist & MLE interview problems
  • We also offer ML system design guides for production-ready solutions.