Is it necessary to get a masters degree for industry jobs in Machine Learning or AI? I’m about to enter my ultimate year of a physics BSc at a top university in the UK, and have done a computational physics  internship with a research group at the university and am currently doing an internship at Harvard that requires strong machine learning skills. I was hoping this would be enough qualification to justify being able to get an entry level job in ML or AI and use that to one day lead myself into a job working with DeepMind, OpenAI, IBM Watson - places like these. I also have some fantasies about working in game design randomly, although I think that needs less a graduate degree and more a portfolio of coded games perhaps. 

However, with those ML and AI jobs I was citing, does it behoove me to get a graduate degree if I want to one day get hired by them? I personally am quite drained from exam stresses and don’t think academia suits me as much as I used to think it does, but if it’s necessary for my goals in industry it might be worth considering.
It depends, I think, on what sort of job you want. For people in the trenches, even at IBM/Watson, an undergraduate degree is probably enough to get hired. You would likely be a team member building things at the direction of a manager. Creativity would be in the "how to do this" rather than in the "what do we need to build" area. 

However, at the level of doing research at IBM, and I assume others, the requirements look a lot like they would for an academic position. Lots of the people there have doctorates, actually. I don't know that a PhD is necessary to get hired, but the more education you have, the better your chances. 

I know people at both these sorts of levels at IBM and at Oracle. 

It used to be that at IBM the trench types could get a doctorate paid for at the company, but that option has disappeared for a while now. They might be a bit flexible about giving you some time-slack to do it, depending on the manager, but funding is unlikely. 

At smaller companies and especially at startups it is probably much more flexible, but also risky. I also know people doing interesting things at such small software shops who have a more basic formal education though they are good at learning on their own and staying at the forefront.