I am currently working as a software engineer at a big tech company which I have about a year in. I am currently thinking of steps I should take to prepare myself in the next few years to apply for a PhD in CS for evolutionary computation or other branches of ML as I always planned on pursuing after a stint in the industry.
For background, I graduated a year ago with a bachelors and masters in computer science from the same university with a concentration in ML, and graduated with the top GPA for my masters, however I did not do any research publications. The extent of my research during my masters was writing papers and doing research for my courses, but they were never published although some of my professors did suggest I should’ve published them at the time.
I looked on here and online and see that this is a weak spot for me. As such, I am asking this question as I feel it would make sense to take advantage of my current situation to get some experience before going for a PhD, since I’m not sure I would have a good time getting admitted into a program being that I am a non-traditional case.
My question is: should I try pivoting my career to get some research experience at a research lab in the industry, like Google Brain or Meta AI, before trying to apply for one of the more top PhD programs? Are there other career moves or general things I can do to help with the lack of research I have? What are some common features of admitted people who came from the industry?