Machine Learning Engineer

A machine learning engineer is the professional who takes artificial intelligence ✕ Artificial intelligence is a computer system’s ability to perform tasks we associate with human intelligence, such as understanding language, recognizing images or making decisions. More in the glossary → models from the lab into the real world. They sit between data science and software engineering: taking models that often begin as prototypes and turning them into reliable, fast, scalable production systems able to serve many users without failing. The work includes preparing data pipelines, training and optimising models, integrating them into applications through code and APIs ✕ An API is a set of rules that lets two programs talk to each other. It works like a go-between that carries requests from one application to another and returns the response. More in the glossary → , and monitoring that they keep performing well over time — a discipline known as MLOps. They need solid programming skills — especially Python — plus foundations in mathematics and in infrastructure like containers ✕ A container packages an application with everything it needs to run — code, libraries, dependencies — in an isolated bundle, so it behaves the same in any environment. More in the glossary → and the cloud ✕ "The cloud" refers to services and storage that run not on your device but on external servers on the internet. You can access them from anywhere. More in the glossary → . With the expansion of AI, it is one of the most sought-after and best-paid technical roles.