If you are serious about deep learning I would recommend this book instead: http://www.deeplearningbook.org It is coming out next month, but you can view the entire book online.

I work full-time as an ML Engineer at a big tech company in Silicon Valley. I think most ML Engineers do not read papers and do not do low level programming. They mostly do feature engineering.

Actually I feel like I forgot a lot of math since university and I would like to pick it up again. Does anyone have a resource they can recommend either for self-study or in person?

Khan Academy is good. Also http://patrickjmt.com/

I'm reading this one math book by Richard Hamming: https://www.amazon.com/Methods-Mathematics-Calculus-Probabil...

Not sure if that's what you're looking for, but it seems to have all the stuff I forgot from college.

Disclaimer: I am the author of this Top-down learning path. Could you please take a look and give me some advice? Or If you have any opportunities, please drop me a line.

My advice would be to figure out what you want to do more concretely. Machine Learning / Data Science is a big field, if you have more concrete goal I think it would be easier.

I personally don't do a lot of feature engineering and I do regularly read papers, I just don't think that I am typical.