Data/ML/AIHigh signal
Reinforcement Learning
Also written as RL
A machine learning approach where a model learns by taking actions in an environment and getting rewards or penalties for the outcomes, gradually improving its strategy through trial and error — rather than learning from a fixed labeled dataset.
Think of it like
Like training a dog with treats — it isn't shown a labeled rulebook, it just learns which actions tend to earn a reward and repeats those more often.
Junior or senior?
Junior sounds like
Has only studied reinforcement learning conceptually.
Senior sounds like
Has worked on a real RL system and can describe the reward signal and what happened when it was poorly designed.
Ask them
“What was the reward signal in a reinforcement learning system you worked on, and what happened when it was poorly designed?”