How to Crack AI/ML/GenAI Interviews in 2025?

Your complete guide to crack AI/ML/Gen AI engineering Interviews in 2025

How to Crack AI/ML/GenAI Interviews

Hello guys, breaking into the world of AI, Machine Learning, and Generative AI in 2025 is both exciting and challenging, remember the $750K offer secured by an ML Engineer story I shared earlier.

The demand for AI/ML engineers, data scientists, and GenAI specialists has skyrocketed, with companies across industries — from big tech to healthcare to finance — integrating AI into their products and workflows.

At the same time, interviews for these roles have become more rigorous and multi-dimensional, testing not only your coding and problem-solving skills but also your understanding of ML system design, data pipelines, scalability, model deployment, and ethical considerations of AI systems.

A typical AI/ML/GenAI interview today is not just about solving LeetCode-style problems or answering theoretical ML questions. Instead, it’s a blend of core CS fundamentals, machine learning algorithms, system design for large-scale AI applications.

As well as practical knowledge of generative AI frameworks like transformers, LLMs, vector databases, and retrieval-augmented generation (RAG). Interviewers want to know if you can build scalable AI systems, optimize models for performance, and think critically about trade-offs in real-world AI products.

Earlier, I have shared best System Design courses, books, websites, newsletters, cheat sheets, mock interviews, as well as ML System Design resources, and today I am going to share steps to crack any ML/AI/Gen AI Interviews in 2025.

By the way, If you are short on time and want a comprehensive, structured resource that covers both ML System Design and Generative AI System Design, I highly recommend ByteByteGo.

how to prepare for AI Engineer interview

Their platform is widely trusted by top engineers and now includes a specialized AI/ML/GenAI interview prep track.

The best part is that they’re currently offering a 50% discount on their lifetime plan, which makes it a valuable investment if you want to fast-track your prep and learn from high-quality visual explanations, case studies, and design problems tailored for 2025 interviews.

System Design · Coding · Behavioral · Machine Learning Interviews

How to Prepare for ML/AI/Generative AI Interviews in 2025?

If you are studying so hard for AI / ML interviews, but just can’t crack them then you are not alone as I am receiving a lot of emails about how to go about preparing ML/AI interviews.

If you’ve been in this situation, it’s time to break free from the traditional prep loop. In 2025, recruiters want real skills, applied knowledge, and problem-solving ability — not just textbook answers.

This is your no-BS guide to preparing for AI, Machine Learning, and Generative AI interviews — and actually landing the job.

1️⃣ Solve Coding Problems — Every Single Day

This is where most candidates fail before they even get to the “AI” part of the interview.

Every company, from startups to FAANG, will ask at least one DSA (Data Structures & Algorithms) or problem solving question — sometimes more.

Core Topics You Must Master:

  • Arrays, Strings, Hashmaps
  • Sliding Window, Binary Search, Two Pointers, fast and slow pointer, Prefix Sum, Frequency Map
  • Matrix Traversal, Graphs
  • Dynamic Programming (optional but very valuable)

Your Goal:
🎯 2 DSA questions per day → 60/month → massive confidence boost.

Recommended Resources:

2️⃣ Build Projects That Teach You AND Impress Recruiters

Forget “Hello World” AI projects and MNIST digit classifiers.
In 2025, recruiters want to see end-to-end, production-ready AI solutions. Show the projects you have built via links or GitHub repo.

Project Ideas That Get You Hired:

  • Resume Screening Bot using LLMs to match candidates to job descriptions.
  • Fake News Detector pulling from live RSS feeds and classifying in real-time.
  • Multi-label Tag Predictor for articles, products, or videos.
  • Semantic Search App using embeddings + vector databases like Pinecone or Weaviate.

Your Cycle:
Build → Deploy → Document → Share (LinkedIn / GitHub / Reddit / X)

Recommended Resources:

3️⃣ Master ML System Design — Non-Negotiable

Machine Learning System Design questions are now standard in mid-to-senior interviews. They test whether you can think like an engineer, not just a model trainer.

Example Prompts You Might Get:

  • “Design a system that summarizes customer support tickets in real-time.”
  • “How would you deploy a scalable LLM-based assistant?”

Key Skills to Demonstrate:

  • Breaking problems into small, logical components
  • Identifying edge cases & evaluation metrics
  • Making trade-offs (accuracy vs. latency)
  • Designing for scale, drift, and retraining

Pro Tip: Keep a personal repo of 10+ system design case studies with diagrams.

Recommended Resources:

4️⃣ Put It All Together — The 2–3 Month Routine

If you keep this disciplined routine for 2–3 months, you’ll be interview-ready and confident.

Daily Routine:

  1. DSA practice → 1–2 problems/day
  2. Project work → push to GitHub regularly
  3. System Design → one case study per week
  4. Knowledge Sharing → post learnings on LinkedIn/X

Bonus: Stay updated with the latest AI frameworks (LangChain, LlamaIndex, vLLM, Ray Serve) and deployment tools (Docker, Kubernetes, AWS Sagemaker).

credit — ByteBteGo

Final Word

That’s all about how to prepare for AI/ML/Gen AI Interviews in 2025. As I have said before, AI/ML/GenAI interviews in 2025 are about practical engineering + applied intelligence.

If you focus on DSA + Real Projects + System Design, you’ll stand out from the flood of “ML enthusiasts” who only watch YouTube tutorials.

The companies hiring in 2025 want builders, not just learners — so start building today.

Other System Design Articles and Resources you may like

Thanks for reading this article so far. If you like these Machine Learning interview tips then please share with your friends and colleagues. If you have any questions feel free to ask in comments.

P. S. — If you just want to do one thing at this moment, join ByteByteGo and start learning Coding patterns and System Design Concepts and practice coding interviews you will thank me later. It’s one of the most comprehensive resource for coding interview now.

System Design · Coding · Behavioral · Machine Learning Interviews

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