AI & DATA
Machine Learning Engineer
Turn models into products that work in production.
What you actually do
Train and evaluate models
Build ML models and measure whether they actually perform well.
Put models into production
Make sure a model keeps working reliably at real-world scale.
Iterate based on real results
Improve a model using live performance data.
Skills you'll use
Tools
You might love it if…
You want to combine strong engineering with genuine ML depth.
Think twice if…
You want pure research without production engineering responsibilities.
How to get there
Learn ML fundamentals and Python
Understand how models are trained, not just how to call an API.
Ship a model into a real product
Go beyond a notebook — deploy something that serves real requests.
Related careers
CAREER PATH
Build my Path
Get a step-by-step plan — Understand, Build, Experience, Prepare.
4 stages · Self-paced
Roles differ by company, team and country. This page describes typical work to help you explore — it isn't a job guarantee, and your day-to-day may look different.