As an ML engineer, you're first expected to have a good understanding of general software engineering concepts, and in particular, basic algorithms and data structure.
Depending on the company and seniority level, there are usually one or two rounds of general coding interviews. The general coding interview is very similar to SW engineer coding interviews, and one can get prepared for this one same as other SW engineering roles.
At this time, leetcode is the most popular place to practice coding questions. I practiced with around 350 problems, which were roughly distributed as 55% Medium, 35% Easy, and 15% Hard problems. You can find some information on the questions that I practiced in Ma Leet Sheet - Yea I tried to have a little bit fun with it here and there to make the pain easier to carry :D (I will write on my approach to leetcode in the future.)
I was introduced to educative.io by a friend of mine, and soon found it super useful in understanding the concepts of CS algorithms in more depth via their nice visualizations as well as categorizations. In particular, I found the Grokking the Coding Interview pretty helpful in organizing my mind on approaching interview questions with similar patterns. And the Grokking Dynamic Programming Patterns for Coding Interviews with a great categorization of DP patterns made tackling DP problems a piece of cake even though I was initially scared! Educative team released a new course for cracking the ML interviews w.r.t System Design Grokking the Machine Learning Interview.
Remember: Interviewing is a skill and the more skillful you are, the better the results will be.