[cerrelio]

The important thing about the PhD is that you've become an expert in conducting experiments and research. It really doesn't matter what ML techniques you've done, as long as you know everything else associated with building those types of systems. Just hone your research and experimentation skills and you'll be fine.

I do have one suggestion: learn to handle dirty data.

I work with ML researchers and notice two things: they're pretty bad software engineers (no knowledge of software patterns, bugs galore), and they almost never know how to clean their data. The latter is because they do a lot of their research using pre-cleaned, standard data sets. You never get that in industry.