Becoming an ML engineer is about 6 months of work for a competent backend engineer. But becoming an X-Scientist (Data/Applied/Applied Research) is a whole diff

Becoming an ML engineer is about 6 months of work for a competent backend engineer. But becoming an X-Scientist (Data/Applied/Applied Research) is a whole different skill set. Now, this kind of role only exists in a proper ML company. But, just acquiring the Statistics & Linear Algebra 201 level intuition is about 6 months of fulltime study in its own right. You also need to have deep skills in one of the Tabular/Vision/NLP/Robotics areas and get hired into a role accordingly. Usually 1 year intensive masters level is good enough to get your foot in the door, with the more prestigious roles needing about 2 years of intensive work with some track record of State-of-the-art results on 1 occasion. Then you have proper researchers, and that might be the most impossible to get in field right now. I know kids who have only done hardcore ML since high school, who are entering the industry after their masters or PhD. I would not want to be an entry level researcher right now. You need to have undergrad math-CS dual major level skills just to get started. They're expected to have delivered state-of-the-art results a few times just to be called for an interview. I'd say you need at least 3 years of fulltime effort if you want to pivot into this field from SWE.