Some questions can also be presented in the form of a simple case exercise such as how would you process a dataset for training and how would you decide what model to use. Interviewers at all rounds will always ask follow-up questions to your answers so if you suggest an idea or approach, be sure you are familiar with it. They may also ask you about keywords you wrote on your resume. For example, if you wrote “GANs” somewhere on your resume, don’t be surprised if they ask you to explain GANs to them in detail with a bunch of follow-up questions. Make sure you brush up on fundamentals of ML and statistics Science Case study Describe how you will generate your dataset: how you will select an unbiased sample, deal with class imbalance, consider temporal effects. How will you split into train/val/test? I follow this website: https://mlengineer.io/
Scientist Interview Questions
61,204 scientist interview questions shared by candidates
Can I call you tomorrow?
Random pick with weight, LeetCode 528
Serialize and deserialize a BST.
How to design the transportation network for warehouses
What neural network architectures are you familiar with
How did u handle failure?
How do you evaluate Gen AI models?
This ridiculous screening test with many random unrelated questions
1. basic and from resume 2. from resume 3. presentation 4. ML depth 5. LP 6. Coding round 7. ML Breath 8. HR -- LP
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