The real solution to your problem is to get another job. And I will disagree with some of the other posters that a PhD is required for ML because that is not necessarily true. I have a BS/MS in applied math and do research into how to apply ML into engineering automation problems for a fortune 50 manufacturing/eng company. Granted, we are not pushing the bounds of ML research. But we are looking at unsolved problems and using ML, control theory, robotics, etc to solve them.
This is what you want. And yes it is very math/algorithms heavy. Whenever we try to hire more people, HR sends us tons of BS cs guys that are sorely lacking the math background. Most of our hires are engineers (mech/ee/comp/aero) or oddballs with math/physics/ computational science like me.
So you can certainly look for other jobs (and if you want I will look at a resume to give more specific feedback). But if you already know that you don't have the background for controls and ML.. then go get it!
Here's the thing with CS or compEng PhDs. You don't have to finish them to get tons of valuable knowledge and move into the 'cool jobs' out there. But (per the rest of this HN thread) if you happen to get an awesome advisor and team relationship then you might as well finish.
Once you are in a PhD program, be upfront with your advisor about this goal and you will likely have an easier time graduating than those students that claim they want to become professors. Typically, to get a PhD you just need to finish your coursework (fairly easy) and produce about three published papers (can be brutally hard or fairly straightforward depending on a ton of factors). The latter's ease also depends on your tolerance for disappointment, because the rewards and successes in research are somewhat sparse.
A lot of the problems people have with the PhD is that there aren't enough academic jobs. You aren't seeking one, so you will be fine as long as you focus on your goal and maintain a good work-life balance most of the time throughout school (this can be very challenging to do, in practice).
A PhD usually requires you to come out of "code-it-up" mode. You clearly have to state a sufficiently scoped problem, why it hasn't been solved before and why your solution can claim to solve it.
If you are looking for more interesting jobs, it is easier just to switch companies. Many RnD companies don't exclusively hire PhD candidates. All the best :)
I'm doing a PhD myself right now in Machine Learning / Deep Learning. I started half a year ago. I don't have any bad experience yet. But I haven't heard too much bad things at all in Germany. My chair: http://www-i6.informatik.rwth-aachen.de/