How to become a machine learning engineer in India: the path I'd actually take
Most guides to becoming an ML engineer in India are a list of courses and a promise. Here is the honest version from someone who hires for these roles and wrote books on the subject: it is one strong project, not ten certificates, and the hardest part is the part nobody sells you a course for.
If you are a student in India trying to become a machine learning engineer, you are drowning in advice, and most of it is a list of courses ending in a promise. I hire for these roles and I have written two books on building ML into real applications, so let me give you the version I would give a younger version of myself, which is shorter and less comfortable.
First, the titles, because India confuses them
Data analyst, data scientist, ML engineer, and AI engineer get used interchangeably here, and they are not the same job. The analyst answers questions with data. The data scientist builds models to make predictions. The ML engineer takes those models and makes them run reliably in production, which is mostly software engineering with ML in the middle. If you like building systems, aim for ML engineer, and know that it means you need to be a strong programmer first and a modeller second. A lot of people fall in love with the modelling and never learn the engineering, and then wonder why the product companies do not call.
The foundation that actually matters
Programming, in Python, until it is boring. The math you can pick up as you need it, but you cannot fake being able to write clean code that other people can run. Then the ML basics, enough statistics to know why a model overfits and what a train-test split protects you from, and enough of the standard toolkit to build something real. That is it for the base. You do not need ten courses. You need one solid course and a lot of building, because the courses teach you the vocabulary and the building teaches you the job.
The thing that gets you hired, and the trap
One project you shipped and can explain beats a wall of certificates, every single time I have screened a resume. The trap in India is the certificate treadmill, the belief that the next course is the thing standing between you and the job. It is not. The thing standing between you and the job is that you have never built something end to end and watched it break. So build one thing, ideally solving a problem you actually have, get real messy data instead of a clean download, and put it somewhere a person who is not you can use it. That project is worth more than the treadmill, and it is the story you will tell in every interview.
Product, services, or startup
The Indian market gives you three doors and they are not equal for this goal. The large services companies will hire you and often park you in work that is not ML, and years pass. The product companies and the startups are where you actually do the work, and they hire on evidence, which loops back to the project. If your goal is to be an ML engineer and not just hold the title, bias hard toward product and startup roles, even smaller ones, over a big-name services offer that puts you on a support desk.
None of this is fast and none of it is a secret. Be a real engineer, build one thing that is genuinely yours, and be able to explain the decisions you made in it. Do that and you are ahead of most of the resumes I see, certificate count notwithstanding. The field rewards people who build, and it is remarkably honest about it once you get past the first filter.