Machine Learning
Also written as ML
Building systems that learn patterns from data to make predictions or decisions, rather than being explicitly programmed with rules.
Think of it like
Like teaching by example instead of writing an exhaustive rulebook — showing a system thousands of past cases and letting it learn the pattern itself.
Junior or senior?
Junior sounds like
Has only trained models in notebooks.
Senior sounds like
Has taken a model into production.
Ask them
“Have you taken a model into production, or has your ML work stayed in research/notebooks?”
Sounds like real experience
Describes a specific model, dataset, or production issue — a feature that didn't generalize, a model that degraded over time — not just familiarity with ML concepts.
Probe further if
Speaks about ML in general, textbook terms — naming algorithms or paradigms — without describing a specific model or dataset they actually worked with.