You need to find an employer who is hiring based on potential or potential + a track record in a different area. I wouldn't hire an ML practitioner with no practical experience. I would hire someone who's produced in other areas and is looking to make the move to a junior ML practitioner (or who has domain expertise in our corner of the world).. It's like the rest of engineering... just because you've taken a course in Python doesn't make you a software engineer or proficient in it. Now show me that you've done things in other languages and we can start talking. Like, courses in ML don't _really_ teach you about things like:
* reproducing model training
* deployment of experiments in a CI/CD pipeline
* observability of models
* discoverability and governance of results
* versioning of data / models
* optimizing for latency vs throughput
* when to use batch vs real time
etc
Just like a course in a computer language wouldn't necessarily teach you about CI/CD, horizontal vs vertical scaling, or domain-specific bits.
Just seeing this. This is exactly right ime, I had years of senior full stack SWE experience /track record of SWE at my employ and was able to get myself on a RNN project initially, then expanded from there. I didn't get hired at a new company as an ML person out of the gate.
* reproducing model training * deployment of experiments in a CI/CD pipeline * observability of models * discoverability and governance of results * versioning of data / models * optimizing for latency vs throughput * when to use batch vs real time etc
Just like a course in a computer language wouldn't necessarily teach you about CI/CD, horizontal vs vertical scaling, or domain-specific bits.