Mechanical Engineering > Master in Financial Engineering/FinMath/etc....

A bit of a crosspost from Quant Net. 

Hi all, I'm looking for an honest review of my profile and some sanity checks. 
Undergrad: BSc - Mechanical Engineering (Top 3 Canadian School, English based), 3.6-3.7 graduating GPA, Jan 2021
GRE: 169 Q, 161 V, AWA 4
Internship Experience:
-Machine Learning Research Assistant - Built various neural network models in Python (Tensorflow/Pytorch focused) (Computer Vision) working with the professor. 2-3 published work including conference/poster abstract/paper etc, 1 first author on conference/poster abstract, 1-2 second author on papers, not sure if this helps at all.
-Big Oil/Supermajor internship - Optimization type of role. Some data science projects but nothing extremely quant/programming like above. Some project cost/evaluation NPV etc but not really "real" investment work.
-Public Sector Project Financing - Typical finance modelling etc but nothing super spectacular or out of ordinary.
CFA L1 anticipated in Dec 2020.
My goal is to end up in Quant Strategy, Portfolio Management, etc preferably in a machine learning approach based role. I really genuinely like working with optimization problems, programming and statistics.
Currently, this is my breakdown of programs that interest me:
CMU MSQF, MIT MFin, Columbia MSOR/MFE, Cornell MFE(I technically don't meet one of the stat requirements but I am happy to take the prereq if accepted). UChicago FinMath
Am I being reasonable here? I constantly feel like I am reaching far too much and I have no business applying to these elite schools. Are there any other programs that I should consider? I do want to be a bit more aggressive here as I would rather to go to US than consider Canadian schools. Furthermore, I am applying to more standard machine learning/EE type of programs in graduate studies in the US. 
Thank you so much for you guys' time and stay safe in COVID.