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RLHF needs experts on tap. A 16-year-old with chess or coding skills can earn real money — here's the truth about the gigs.
OpenAI, Anthropic, and Google pay people to write good answers, rank model outputs, and judge AI mistakes — this is RLHF (reinforcement learning from human feedback). Expert annotators on platforms like Scale AI's Outlier, Mercor, Surge, and Invisible earn $25-100/hr. Pay scales with the rarity of your skill: a teen who codes well, plays chess at a high level, knows AP Calc cold, or speaks a less-common language can qualify. The work is real, the pay is real, and the age requirement is usually 18 — but Mercor lets verified minors apply with a parent.
Make a one-page 'skill resume' tonight: list one to three verifiable skills with proof links (Codeforces handle, App Store URL, AMC score). That's the application packet for every platform.
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-careers-ai-data-annotator-mercor-scale-r10a10-teen
What is the main idea of "How Teens Make $30-100/hr Training AI on Scale and Mercor"?
Which concept is most central to "How Teens Make $30-100/hr Training AI on Scale and Mercor"?
Which use of AI fits this topic best?
What should a careful learner remember about "The rule"?
You want to use AI after this lesson. What is the safest next step?
How should AI output about RLHF be treated?
Name one way to verify an AI answer about RLHF.
Which action would help you apply "How Teens Make $30-100/hr Training AI on Scale and Mercor" responsibly?