Hiring trends, salary data, and whether the title survived the hype cycle—or dissolved into every other tech role.

A former contractor for a major social platform spent six months reviewing flagged videos and posts. They requested anonymity due to an NDA and fear of industry retaliation.

Why companies hire workers to manufacture artificial training data, what the role pays, and how it differs from traditional labeling.

Displacement patterns by sector, timeline evidence from hiring data, and roles absorbing workers as automation compresses headcount.

RLHF raters, AI red teamers, prompt engineers, and MLOps roles—defined with entry paths, skills, and income bands for the post-2020 labor market.

Beyond the buzzword—daily tasks, tools, career paths, and the gap between recruiting language and shift reality.

I spent two weeks trying to earn a living on microtask platforms—Mechanical Turk, Appen, Clickworker—and tracked every cent, every rejected batch, and every bot competing for the two-dollar tasks.

Hourly pay, contractor status, and the mental health toll of reviewing violent and abusive content for platforms that rarely discuss moderator wellbeing in job postings.

Piece rates, hourly averages, and what full-time labelers actually take home after taxes, idle time, and unpaid rework.

AI first-pass classifiers, human review queues, policy bibles, and wellness programs that rarely suffice—how platforms filter billions of posts before users see them.