Review — Is Machine Learning System Design Interview Worth It?

Is Machine Learning System Design Interview by Ali Aminian & Alex Xu worth reading?

Hello guys, when it comes to preparing for machine learning (ML) system design interviews, many candidates quickly realize that knowing algorithms and models is not enough.

Companies like Google, Amazon, Meta, and other large tech firms don’t just want to see if you can train a model; they want to see if you can design a scalable, reliable, and efficient machine learning system that works in the real world.

This is where books and structured guides become invaluable, and one of the most popular resources in this space is Machine Learning System Design Interview by Ali Aminian and Alex Xu.

Machine Learning System Design Interview

If you’ve heard of Alex Xu, you’ll know him as the author behind the well-regarded System Design Interview books and the co-founder of ByteByteGo, a platform dedicated to helping engineers crack coding, system design, and ML interviews.

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Together with Ali Aminian, an ML engineer with deep industry experience, they created a focused guide to help ML engineers and data scientists succeed in one of the toughest rounds: machine learning system design.

But the big question remains: is this book actually worth your time and money? Let’s dive in.

What does the Book Cover?

Machine Learning System Design Interview provides a step-by-step framework to approach ML system design questions, making it especially useful if you’ve never faced these types of interviews before.

Some of the key highlights include:

Structured frameworks for answering open-ended ML design questions.
Case studies of real systems such as video search, visual search, recommendation engines, and harmful content detection.
Coverage beyond just models — dataset collection, feature engineering, metrics, model serving, scaling, and monitoring.
Clear diagrams and visuals to help you communicate effectively in interviews.

You can check it out on Amazon here.

Machine Learning System Design Interview

Strengths of the Book

Here are the strong point of books which also separate it from other Machine Learning interview books I have shared earlier.

Clear Structure
The book gives you a repeatable framework so you don’t get lost when faced with vague interview questions.
Realistic Case Studies
Each example reflects challenges you’ll face in practice, from recommendation engines to fraud detection systems.
Focus on the Full ML Lifecycle
Unlike many interview resources that stop at models and algorithms, this book emphasizes data pipelines, serving infrastructure, monitoring, and trade-offs.
Great Visuals
The diagrams make it easier to both understand and present your answers — a skill interviewers really value.

It also cover many case studies and solution of popular ML Engineering interview questions.

Overall a great resource to prepare for ML System Design interview and the best thing is that this book is now available on ByteByteGo along with Alex’s other System Design books

And, you can now get ByteByteGo lifetime plan for 50% OFF as well, I just bought it and I highly recommend it because then you can use this resource anytime you go for interview.

Here is the link — join ByteByteGo with 50% Discount

Limitations — What Could be done better?

No single book can cover every angle of ML system design, and this one has a few gaps:

It doesn’t go extremely deep into cutting-edge or specialized ML infra (e.g., distributed training, edge ML, or large-scale data engineering pipelines).
It assumes you already have a baseline understanding of ML fundamentals. Beginners may need to start with core ML resources before diving in.
Real interviews often include unexpected constraints or product trade-offs, so you’ll need additional mock interview practice alongside reading.

You can actually combine this book with mock interview platforms like Exponent and DesignGurus.io for better preparation. I highly recommend mock interviews for best results.

Who Will Benefit Most?

Here are the folks I think will benefit most from reading this books:

New grads / junior ML engineers: Very high benefit. The structure and examples help avoid common mistakes and give you confidence.
Mid-level engineers: High benefit. You’ll sharpen your system thinking and learn to communicate designs effectively.
Senior ML engineers / specialized roles: Moderate benefit. It’s a good refresher but you’ll need to supplement with research papers, production experience, and deeper system design knowledge.

If you fall in one of these categories or genuinely want to improve your knowledge of System Design and in particularly machine learning System Design then you can also read this book.

Here is the link to get the book — Machine Learning System Design Interview

Comparison with Other Resources

So how does Machine Learning System Design Interview stack up against other prep materials?

System Design Interview books (by Alex Xu) — These are great for general system design but don’t cover ML specifics. If you’re preparing for ML roles, you’ll need the ML-focused book alongside them.
Designing Machine Learning Systems by Chip Huyen — This book goes deeper into real-world production ML systems and MLOps, but it’s less focused on interview preparation. It’s great as a complement.
Courses like Exponent or DesignGurus ML System Design tracks — These give you practice via mock interviews, which is something a book alone can’t provide.
ByteByteGo Platform — The book is excellent on its own, but ByteByteGo’s online platform takes it further with videos, weekly system design deep dives, and ML design case studies. It’s more interactive and helps you practice at scale.

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If you want a complete package, I’d strongly recommend pairing the book with the ByteByteGo platform, especially now that they’re running a 50% lifetime discount.

With that, you get access not only to ML system design content but also to coding interview prep, general system design guides, and weekly updates that keep you ahead of the curve.

You can check it out here: ByteByteGo Platform — Lifetime Plan (50% Off).

Is Machine Learning System Design Book Worth It?

Yes — Machine Learning System Design Interview is definitely worth it if you’re serious about preparing for ML interviews in 2025 and beyond.

It gives you structure, real examples, and a strong foundation for thinking through ML system problems in a clear, interview-ready way.

That said, the book works best when paired with practice and complementary resources.

For the best results, use it together with mock interviews, deeper ML systems references, and platforms like ByteByteGo, which expand the coverage and provide ongoing updates.

If I were preparing for ML interviews at FAANG-level companies in 2025, I would make this book my starting point and then supplement it with ByteByteGo’s lifetime package — especially while the 50% discount is available. It’s one of the smartest investments you can make in your interview prep journey.

👉 Get the book here: Machine Learning System Design Interview (Amazon)
👉 Explore the full platform: ByteByteGo — 50% Lifetime Plan

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Other System Design and Coding Interview and Resources you may like

All the best for your System Design and Machine Learning interview preparation , if you have any doubts or questions, feel free to ask in the comments.

P. S. — If you just want to do one thing at this moment, join ByteByteGo and start learning software architecture fundamentals and 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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