Advice on becoming a research engineer [D]
Summary
A software engineer with 40+ years and staff-level experience seeks advice on transitioning to a research engineer role, discussing the realistic prospects, required experience, and strategy options given their strong technical background but limited recent applied ML work.
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.
Similar Articles
Tier-3 ISE final year with ongoing ML research (TMLR/Q1/NeurIPS target), trying to understand real impact in India [D]
A tier-3 college final-year ISE student with ongoing ML research publications (TMLR, NeurIPS targets) seeks advice on the practical value of research credentials for industry jobs in India and higher studies abroad, versus traditional DSA/dev focus.
How does the ML community view evolutionary algorithm research? Career implications of an EA PhD? [D]
The author asks about career implications of pursuing a PhD in evolutionary algorithms for the ML community, discussing whether it limits opportunities compared to a more ML-centric PhD.