I also dont understand what you mean by "exceedingly high value work". For both production as well as research (ICML/NIPS/CVPR) the languages used are in most cases Python/C++/Lua.
Also Stats PhD (who I believe are the sole users of R) aren't typically hired into Machine Learning roles.
R is okay for wrangling tabular data, applying statical model for hypothesis testing and generating pretty charts for papers. But not suitable for state of art Audio, NLP, Vision or Reinforcement Learning.
FWIW, I used R for my undergrad, and still use R for personal projects afterwards. (with modern R, dplyr/ggplot2 are an order of magnitude easier to use, in my opinion, than the Python equivalents)
This is very different than trying to recognize street signs.
For the person who downvoted me, I wasn't saying R is better than Python. I was just saying that if you have just R, you're probably not doing data wrangling..
What this post is completely failing to capture is the exceedingly high value work in machine learning versus the typical work any skilled undergrad can do.