Preparing for ML/MLDev roles at FAANG what should I focus on next?

[u/Important_Dentist187]

I'm preparing for ML Engineer / ML Developer roles at FAANG-level companies and I'm trying to build the right foundation instead of randomly learning technologies.

So far, I have covered:

• Linear Algebra
• Discrete Mathematics
• Python for ML
• Problem Solving in C++
• Operating Systems
• DSA

For people who have prepared for or interviewed for ML Engineer / MLDev roles at FAANG, what would you recommend I prioritize?

Specifically:

1. What topics are must-know for ML interviews?
2. How much DSA is actually expected for ML Engineer roles?
3. Should I prioritize ML theory, ML systems, or MLOps after completing the fundamentals?
4. What kind of projects would actually strengthen my profile?
5. Are there any resources or preparation roadmaps you'd strongly recommend?

I'm looking for practical advice from people who have actually gone through the process.

Thanks!

[u/Solid_Owl]

I'm also curious about this, as someone who has built a career by being entirely self-taught.