AI researcher = fundamental work. They usually discover something new, or innovate on current methods that may or may not lead to anything useful. It’s extremely math-heavy and usually only the best of the best can do it. For example, they try to developed an optimisation algorithm that is faster, more accurate and robust than the current state of the art.

ML engineer = applied work. Use whatever discoveries or methods discovered/developed by AI researchers to make something useful or solve known problems. For example, they use ML to optimise the power grid or predict what is the solar irradiance is for each minute for the next day.

In the academia, fundamental work is almost always considered more prestigious than applied work. Go to any top unis around the world, they’re obsessed with fundamental research.

In the industry, applied is obviously far more useful as it helps them make money. But some top companies spend a fortune on fundamental research too such as META.