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I’ve worked at Microsoft as a software engineer three or four times, depending on how you count it. In between I worked at a university, Amazon, Google, and on Oracle Cloud.Microsoft is an interesting place. I always thought of it as a place where you could jump around between projects using any sort of technology without losing seniority or benefits. You’d know the internal tools, corporate environment, and have a steadily expanding group of contacts spreading out through the company you could leverage, while exploring something new.While at Microsoft I’ve gotten to work on:Sound and video multimedia.Core operating system components in Windows used by most everyone.Network security protocols, peer-to-peer protocols, and device control.A triple-A game, flight simulator.One of the world’s largest distributed file and processing systems, Cosmos.An innovative touch-mouse.Gesture recognition using Kinect.A web browser and Win32 layer for unix.An end-user photo application which we productized the framework for and shipped an end-user experience for.Azure compute allocation, which decides where every azure VM is placed in physical servers for all of Azure Compute.In addition there’s programming language design and implementation, IDE systems, office productivity, SQL server, world-wide web servers and e commerce services, and a million other things.While doing this I get better-than-average industry pay, great benefits, a great environment to work in, and the knowledge that every thing I work on can affect anywhere from millions to billions of people, and impact the industry as a whole. Work is flexible. I wake up early (naturally) and it’s not a problem, I come to work at 4 or 5 or 6, and leave when I have put in my time. If I get tired, I leave earlier and make up the time later. I’m surrounded by smart, interesting, and generally nice people and have a great time at work most every day.What part of that doesn’t sound likeable?

I too am an electrical engineer and I think I can offer a different angle on machine learning and career decisions.By the way, the first response to this question was spot on. If you drop out of the work force it can be hard to get back in. Think carefully about this before acting on this.I'm skeptical of machine learning without an application. For example, current hot areas for machine learning span multiple data domains: text, speech, music, image, video, multimedia and there are different applications of machine learning within each domain. For image data alone, you have image recognition, scene analysis, face recognition, optical character recognition and so on. Each area requires slightly different domain expertise. If it were up to me and I was hiring for a position in face recognition, I would hire someone with actual experience in that domain over a machine learning or data science generalist.Therefore I would suggest looking for for the specific career you want that uses machine learning and look to see what kinds of background will help you get on that track.

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