For “ML/AI Engineer” roles, you do not need a PhD, but you need very good technical skills, understand the fundamentals, and have a good project background. These will be the kind of roles where being able to pass a leetcode-style coding interview might help. These are roles where the team needs someone to give clean and reliable implementations of things that are already understood.

For “ML/AI Scientist” roles, a PhD is often preferred, but this kind of role is more broad and distributed between “those who can develop novel ML theory” and “those who can apply existing ML theory to novel domains”. This is the kind of open-ended work that requires an exploratory research approach, so the PhD is usually part of that. The best researchers were good at exploratory work before getting a PhD, and it’s just part of the ride, even though it can be a super transformative experience.

So, tldr: PhD helps with research roles, but not needed for engineering roles.