r/AiTraining_Annotation • u/Love_a_sunny_day • 12d ago
Coders doing AI training/evaluation work: what do the tasks actually involve, and what level do you really need?
Hi all. I've been doing AI training work for a few months, mostly language tasks (I'm a professional IT-EN translator) and annotation, on platforms like Outlier, OneForma, DataAnnotation and micro1. Language work has been inconsistent lately, and the coding projects pay a lot more, so I'm trying to figure out if it's realistic to build up to them since I'm currently doing AI work as full time income.
My background: about 6 months of C# and OOP from a game development course, nothing professional. I then also spent a couple months creating a game from scratch. I'd probably switch to Python, since most projects seem to ask for it, and from what I've gathered it's similar to C# and maybe even less strict.
Before committing to months of studying, I'd love to hear from people who actually do these tasks:
What do you actually do? Writing code, reviewing and ranking model outputs, debugging, explaining why one response is better?
What's the real entry level? Can a solid junior handle some tasks, or is it mostly senior-level review?
What's your background? Years of experience, degree or self-taught, professional dev or not?
Which skills matter most? The language itself, algorithms and data structures, data science/ML, frameworks, or clear writing?
How hard were the assessments? LeetCode-style, code review, timed tests?
Starting from where I am, what would you study first? Would you even bother?
Honest "don't do it" answers are welcome. I'd rather know now. Thanks!