2 min readfrom Machine Learning

Advice on becoming a research engineer [D]

I am thinking about becoming a research engineer, and want to ask your advice on how realistic it is, and which strategies make sense in my situation.

About myself: I am in the US, have extensive experience as a Software Engineer (including Staff+ position at one of the top companies), have a math heavy CS degree, and have taken additional ML courses from one of schools offering them to outsiders. I also had applied ML work some time ago, but I didn't like it (that's why I am considering research engineer position, and not a fine tuner or a prompt engineer). I am also a bit over 40, which I feel might be a problem for some companies/positions.

What organization hiring for these positions are looking for? What kind of experience is required? Which strategies could I use.

P.S. It's realistic for me to invest into unpaid/lower paid positions at least part time, where I could get the required experience.

UPD1: I thought about getting a master degree, but I don't see what it will get me except connections/publications (I have a good base in classical numerical stuff, and covered almost all relatively modern areas of ML with additional courses). Getting PhD doesn't look like a good idea to me, but I might give it a thought.

submitted by /u/ArtisticHamster
[link] [comments]

Want to read more?

Check out the full article on the original site

View original article

Tagged with

#natural language processing for spreadsheets
#generative AI for data analysis
#Excel alternatives for data analysis
#real-time data collaboration
#real-time collaboration
#rows.com
#modern spreadsheet innovations
#digital transformation in spreadsheet software
#financial modeling with spreadsheets
#research engineer
#machine learning
#software engineer
#experience
#numerical methods
#Staff+ position
#PhD
#applied ML
#ML work
#master degree
#jobs