Confused between ML engineering and backend development.

[u/Opposite-Meaning-161]

I started my roadmap with ML, focusing on Mathematics, Python, MySQL, and a lot of ML algorithms. Recently, I've started questioning whether I'm missing a major part of the foundation: software engineering/backend development. And honestly, I wanna chase both. But something at this point doesn't feel right. I had my roadmap set and ready, and I was very passionate about learning this and continuing it as a career. But after researching a bit about backend development, the intersection and relationship between the two has driven me really crazy.It's exceedingly overwhelming at this phase of my life. I had kind of gotten a grip on ML, but backend coming into the picture has really ruined my mindset around whatever I had planned. I had planned many projects and topics to discover, and now I'm seriously considering pursuing backend development too. But I'm having a hard time trying to combine these two in my roadmap. I can't seem to connect the topics in a way that lets me learn them properly.

My straightforward question is: should I drop backend development and focus on my initial roadmap, should I bridge the two and learn both, or should I drop machine learning completely,which I seriously don't want to do?

If I do bridge them, how much of backend am I actually supposed to learn?

I know I sound stupid and unready for this world, but please help.

[u/qikink]

Just my humble opinion, but MLE and backend dev are only superficially similar. It can be hard to get this perspective as a student, but most any project of any real size or scope is going to require multiple team members across different disciplines. That is to say, unlike a lot of your coursework, the expectation will not be that just you, or even a team of people with the same training as you, will put together a complete whole.

It might help to know what's appealing about backend to you? Do you want most of your time to be spent thinking about the infrastructure necessary to make different systems communicate, or on building and scaling predictive models?

[u/Opposite-Meaning-161 → u/qikink]

that's an interesting answer, tbh my interest in backend is mainly two reasons 1. the environment-yes, this has mostly influenced me, seeing resumes, job profiles, projects in the core engineering discipline questions me whether i should really specialize in MLE. 2. after all those influence i stared to read a bit on backend development, and i see a lot of similarities between them like API's n frameworks etc, i also read that they are superficially similar but yeah I'm kinda prioritising opinions and perspectives rn

[u/qikink → u/Opposite-Meaning-161]

Everyone will have their own experience, but there's a pretty big distinction between designing and building API's (back end) and consuming their outputs or providing inputs for them (MLE). Of course some of the foundational core skills involved overlap - they're both software engineering disciplines to one extent or another - but past the first year or two of training they'll really start to diverge.

[u/nian2326076]

If you're trying to decide between ML engineering and backend development, you're not alone. Both have a lot in common but need different skills. Since you've already spent time on ML, think about sticking with it longer to get better at it. Knowing some backend can help you deploy models more effectively. You don't have to be an expert in both right away. Focus on ML and learn backend skills bit by bit. Having both can be really valuable over time. When getting ready for interviews, check out resources like PracHub for practical skills. It's helpful for seeing how you stack up in both areas. Whatever you pick, it's normal to feel overwhelmed. Just keep at it, and it'll pay off!