I took a dataset of 20M job postings from big and small startups. I then used a ML classifier to classify each engineering job to the type of engineer it belonged to (ie backend, ML, date, mobile etc). In addition, I extracted the skills listed in each job using entity extraction. I indexed all of this to an elasticsearch cluster when I ran aggregation queries to see how the # of jobs changed for each type of engineer in the past year.
Here were my findings:
1. The # of jobs for ML engineers and research scientists increased 70% from a year ago
2. # of jobs for frontend, mobile and data engineers all dropped 25% from a year ago, while backend engineers did a bit better dropping at 12%
4. Data scientist jobs and security engineer jobs did a bit better, both declining 5% or so
5. There seemed to be no correlation between tech layoffs and the demand for more AI engineers/talent.
I published my findings in more detail in the article. Of course correlation != causation but just trying to make sense of the data as best as I could. Everything I wrote is still just an opinion, but backed by some data :)