Isn't it 2 profiles of engineers? Those who make production code and those who work in prototypes?
One thing is to understand why your model isn't converging, another is how to scale it up...
- excellence in being able to clean data at the column level for millions of data points - knowing how to work with such large scale data in a time efficient manner. One of our newer hires worked at the Postgres/SSD level to optimize and got it to where he could produce a full set within 5 minutes. Before that it was once every few months.
Being able to do these things is a prerequisite to building even a prototype of a model, and it requires substantial real-world programming experience to deal with those complexities.
- Research departments that make prototypes that are consistently abandoned and never get any real world usage.
- Actual companies that make prototypes for real business cases that are then shipped to production, maintained and improved as they bring in $$$.
The first experience is of limited value to the world of real business.
I'm continually exposed to new kinds of software engineering roles I never heard of at tech companies. (fwiw software engineer is sometimes still considered an inflated title.)