r/Backend • u/Opposite-Meaning-161 • 2d ago
Confused between ML engineering and backend development.
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.
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u/EveYogaTech 2d ago edited 2d ago
The major shortcut for the backend is being able to run docker images with small scripts.
I'm also currently doing that myself with Nyno as well.
Especially since ML is mostly math, you can start with small scripts and experiments, and later call those exportable functions in your backend.
Nyno also has Postgresql already installed for you in the docker btw, might also help a lot, because you can immediately play around with queries using the nyno-sql nodes.
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u/Both-Fondant-4801 2d ago
ML Engineering is fairly new.. 12 years ago, there is no such thing. If you are an engineer working with data, building data pipelines, developing apis.. you are a backend engineer. The first ML engineers were backend engineers who specialized into ML.
so.. in my opinion, you should at least have a grasp of the fundamentals - databases, queus, containers, apis.. before you specialize. you dont need to go deep into backend.. i think just the basics is enough to help you as you specialize in ML.
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u/Conscious_Mark1784 1d ago
I did the exact same thing, like data science -> ml -> deep learning-> ai engineering-> backend , but honestly, no need to go like this way , the data science way is much more research side , u will spend a lot of time , rather than if job priorities, then learn backend get into a field , then spend time ok learning whatever u like
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u/Opposite-Meaning-161 1d ago
Why do u say u needn't go that way
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u/Conscious_Mark1784 1d ago
It entirely depends on u , see i am now graduating, i need a job currently, but guess what ? Most freshers job specially in my country ( 3rd world country) startup companies mostly want to survive and ai thing is highly unpredictable, that is why it is naturally more backend job as a fresher than ai job
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u/pthierry 2d ago
Something is true for all projects, careers or software: if your roadmap says where to go, it means you want to stay a course despite learning things in the meantime. It doesn't make sense.
Having a vision is good. Having ideas on what some steps should follow some other steps is good.
But the fundamental trick is to work in small steps, and be able to adjust after each step. I'm reasonably certain that learning some backend engineering will help you. Some ideas like Hexagonal Architecture, "Make invalid states unrepresentable" or Functional Core/Imperative Shell are relatively simple but extremely useful, way beyond just creating server APIs.
How much backend engineering will be interesting and helpful to you, though, neither of us can say for sure right now.
So my advice would be: learn a few basic things, experiment doing backend, and after that, reevaluate where the next step is.
Maybe you'll want to dig deeper into backend architecture (e.g. REST/Hypermedia APIs) or security (e.g. capability-based security). Maybe doing backend will interest you in frontend. Or maybe it will not be a question of interest but of professional opportunities…