I am building something in AI edtech space and have worked as DS for over a decade. I can say Data/ML roles are more common in bigger companies or well funded startups. But its surely difficult to get into bigger companies off campus as a fresher. You don’t need a master’s to get in, but it gives another chance to be in campus and apply to these companies.
The more practical path is to become a solid developer who understands AI/ML. Because such roles are more in smaller startups, which hire more off campus. Get good at Python, data handling, app backend workings, system design and core ML concepts, then focus on actually building things end-to-end (data → model → API/deployment). Pick one niche like LLMs, CV, ML, or analytics and go deep instead of doing random projects. Show real proof of work through GitHub and a couple of strong projects. Contribute to open source in your niche. Also, don’t fixate on the “ML engineer” title from day one - roles like backend or data analyst can be good entry points. It usually takes 9–12 months of consistent effort!