I am not sure if this is a relevant post here but:
I made it to the final round for the Machine Learing Engineer position at Facebook. The final round interview is virtual (thanks to Corona) and will consist of:
2 - General Algorithmic Coding questions 1 - Machine Learning Design 1 - General Systems Design 1 - Career Background
Most of these I know what I need to do to prepare but the content given to me for the Machine Learning Design is scarce to say the least but typical example questions for these are:
Design a newsfeed ranking algorithm Design local search ranking Design if an old post would be good for "On this Day" memories feature
This is the key highlights of what is expected for the Machine Learning Design interview:
You should be able to describe the components of an end-to-end ML system, including but not limited to; model development, evaluation, and deployment. You should be able to use existing toolsets to model the problem and break down its components. Be ready to analyze your approach while understanding the tradeoffs between your design decisions. We expect you to have a good understanding of common ML tools/techniques, but we do not expect you to know and memorize every ML algorithm out there.
Now, although I know Machine learning decently well (I would like to think so) and I do mainly do Machine/Deep learning at my curreny job. I have never designed a Machine learning system. Thus I am not sure how to prepare for this particular portion of the interview and I have not really found much material online in terms of designing machine learning system.
Any advice would be greatly appreciated. My interview is set in the beginning week of April.