Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

I am a EE, hardware engineer with about a decade of experience in PCB electronics and systems engineering experience which includes a brief stint at a FAANG that also happens to be an E-tailer. I have been "dabbling" in Python for about a year now and just recently started with DL using PyTorch and find it quite interesting. To be clear I don't write code at work, atleast not until now. I intend to utilize any free resources (MOOCs) to teach myself the latest techniques in DL for CV. What I am not clear is the next logical step.A part of me wants to Boostrap a SAAS using Python stack to build something that I can market using the traditional channels(PH,Show HN,Reddit,answer SO questions) and show it to potential employers but am not sure if I will even get to the interview stage with a resume but that doesn't look anything like a programmer with a tradional CS background and work experience to boot. Sorry about the long and winding question, but what should I do to get noticed by recruiters at FAANG and non-FAANG to stand apart from the CS crowd?

I'd say pivoting to ML/AI is much easier for Math/Physics folks compared to pure CS ones.

I've hired about half a dozen ML engineers/architects in the past six months. Several of them have EE backgrounds. There's a good bit of ML that touches on hardware (think integrated cameras and similar) so it can be really helpful.

You're mostly on track with your plan to build something. You do need to demonstrate that you have the skill set, but building one giant thing isn't the answer. There's so much that goes into building a giant thing, that I can't accurately access your ML skills.

Ideally I like to see a lot of small things over a reasonable amount of time. Someone with a solid GitHub showing 6-12 months of paper implementations, weekend geez-wiz hacks and various other projects would go right to the top of my call back list.

Hope that helps, good luck with the job search.

Are you looking to do your own startup or just find a job someplace? The deal with most ML type jobs is that you have to be working at a company that has a need for that sort of thing then pivot into that role because you understand the data really well already. You're not going to find much success any other way.

Thanks for the response.Wireless comms seems like ripe for ML enhancement. PCB inspection is something that has crossed my mind indeed but it is quiet involved due to the sheer number of features ( traces, components, vias, connectors) none of which has pretrained models. Having said that Automation esp FAI( First article inspection) is quiet possible as demonstarted by landing.ai(Andrew NGs) company.Being employee at a publicly trading company, not sure how I can secure funding. Perhaps my focus should be to apply ML directly to something that I do day-day at work.