As a hiring manager for AI/ML, if you can get in the weeds and talk the talk with data structures and pipelines, as well as advanced SQL then you're in with a good chance of making the final list. If you're a humanities major who's just done a few Coursera courses in AI at the weekends, then sorry no.
Software engineers by and large, can make great AI/ML practitioners - the specialization is a smaller leap than say from business analysts or any folks who're less likely to be able to install their own OS or automate task with scripting.
The MLops salaries compared to traditional software engineers are comparable, less/more? I assume the 900k job offers are the post grade researchers only (MS/PhD math etc)
Not just researchers, but theyre for experienced MLOps engineers. If youve built distributed training or inference pipelines at big tech, thats the sort of skillset that requires ML knowledge but has little to do with traditional research.
Those roles where they have "must have PhD in related field" are mostly there as MacGuffins, if you're good enough and obviously know your stuff you're going to get moved on to the next step by and large.
MacGuffin - In fiction, a MacGuffin (sometimes McGuffin) is an object, device, or event that is necessary to the plot and the motivation of the characters, but insignificant, unimportant, or irrelevant in itself.[1]
if you dont mind, resume wise what would make someone stick out when hiring? if they dont have professional experience yet but have done some serious learning. Projects with some substance?
The main thing to realize is that people may take a really short time to look over a resume, maybe a couple of minutes max. So any project you've worked on, needs to be accessible right away so they can check it - in effect you need to quickly spoon feed them something that shows your capabilities.
So, what not to do - provide some 50-slide online project presentation with a complex summary description.
In the absence of professional experience, what I'd suggest is to build some impressive ML/AI projects, ideally something with a running data pipeline in the background, and put them up online along with their source code. Something like this (below) would really catch my eye on any resume, and would definitely generate some click-throughs and interest. If you could then go on to explain how you single-handedly built out the data pipeline, handled and parsed LARGE volumes of data and what you used to generate the output that would be a great step.
You could even game it, by doing a later public analysis of all the click-throughs and interactions, which would be really impressive.
"May - Aug. 2023 - Built out MyStockForecast.com, which delivers a daily forecast for 500 tech stocks using an XGBoost model, and a continued retrospective analysis.
Software engineers by and large, can make great AI/ML practitioners - the specialization is a smaller leap than say from business analysts or any folks who're less likely to be able to install their own OS or automate task with scripting.