Academia vs. Industry for Machine Learning For PhD students in machine learning, academia vs. industry is an increasingly strange choice. Getting a faculty job at a good university is still quite hard, but the pay is hugely lower than in industry (~ 120k for an assistant professor job at a top 10 school, vs. ~ 500k for a research scientist position at Google/FB/Amazon for a similar candidate).
What is the allure of academia? It comes with grant pressure, teaching huge classes, and huge opportunity cost in salary.
Other engineering disciplines can have a vaguely similar pay gap, especially when comparing with a top industry job as you describe (and doubly so when comparing living in SF to a college town)
A common argument is for the freedom offered in an academic job. Another is that industry jobs are often more boring. I think there is also something to be said for being able to potentially &quot;leave your mark&quot; in academia in a way that isn't necessarily possible working an industry job. Lastly, I'll point out that some cultures think very highly of professors, in the same way US culture tends to think most highly of doctors.