So there's definitely opportunities for taking on a role as an ML engineer with a non traditional background. From a learning perspective, I'd say that you cou

So there's definitely opportunities for taking on a role as an ML engineer with a non traditional background. From a learning perspective, I'd say that you could start by taking courses on statistics and probability, then reviewing a little bit of calculus, and then doing something like the machine learning and deep learning courses on coursera. From there you can test out your skills using a platform like https://workera.ai/ https://workera.ai/ For getting raw experience though -- if you aren't in an academic setting, or a technical setting where you could be exposed to those opportunities, the best thing that you can do is contribute to widely used ML libraries on a platform like github. It's definitely not easy to get started in that process, but it'll teach the workflow of a basic ML or research SWE, and you will definitely be a super independent learner or worker after that. Good luck with your journey!