AI Trainer / RLHF Specialist
Growingoperations
Every modern AI model is shaped by humans rating outputs. This is that job. Responses get rated and ranked. The ranks turn into preference data that feeds the RLHF pipeline. The rubrics ask whether a response is accurate, helpful, safe. Most days are slow and careful. Many specialists bring deep domain expertise in medicine, law, or coding, which lets them evaluate model performance in places a generalist cannot.
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A Day in This Role
The queue is the work. Model output comparisons, one after another, scored against a rubric that asks which response is more helpful, more accurate, safer. Midday usually brings a calibration session with other trainers to argue through the tricky edge cases and align on the gray ones. Late in the day, the work shifts mode entirely: writing demonstration data that shows the model how an expert would actually answer a hard question.
Common Interview Topics
- 01You're comparing two model responses to a medical question, one is more thorough but slightly inaccurate, the other is brief but correct. How do you rank them and why?
- 02Describe your process for identifying subtle hallucinations in a model response about a topic you're not deeply expert in
- 03How do you maintain consistent evaluation quality after reviewing 200+ response pairs in a single day?
- 04Walk through how you would write a high-quality demonstration response for a complex multi-step reasoning question
- 05A model response is technically correct but could be misused, describe your framework for evaluating safety versus helpfulness trade-offs
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Career Path
AI Trainers advance into training team lead or quality assurance manager roles at AI labs. Top performers with domain expertise transition into AI safety research, prompt engineering, or AI policy positions.