I recently graduated from my computer science master degree and got a job as an ML Engineer. I am not only interested in pure data science.

Here is how I did it:

1. Realise university doesn't teach the necessary knowledge --> so I did loads of courses and read books to get a foundation.

2. With that knowledge, I was able to get a student job in the ml field. Finding that job took loads of hours researching in job portals.

3. I had a study project for which I was allowed to write my master thesis, including object detection.

4. End of university: Be prepared to move your location. I almost never found an interesting (entry) job in my hometown. It isn't easy to find an entry job, as you said, but they exist. Basically, search on every available job platform. Do your homework and write an appealing application. If you get invited, be relaxed and turn the conversation towards topics you know well. But most importantly, I realised it isn't worth taking a job if you don't vibe with the people you speak to during an interview. You can learn your craftsmanship, but it is incredible hard to work with people you dont like.

Basically, you spend 2-3 months researching and applying to EVERY job you can find, which doesn't sound like they are searching for a unicorn. The best job descriptions are rather short and precise. If they search for a senior don't immediately go on. It is very hard for companies to find a senior. We lost a colleague recently and we already know that we won't find a replacement for at least a year ... and as you might guess the position got replaced by a junior.