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FAQs about Hiring for RLHF and Preference Data
You can hire for pairwise ranking, best-of-N selection, multi-criteria scoring (helpfulness, correctness, safety, tone), response rewrites, failure tagging, and more. Whether you need raters to compare model outputs, score against a rubric, or produce gold-standard demonstrations, you can find experienced specialists in our network.
Yes. Many preference tasks require subject matter expertise to evaluate correctness and nuance. You can hire domain specialists in code, medical, legal, finance, STEM, and other fields. They work alongside generalist raters or on high-stakes slices where domain knowledge matters most.
You define the rubric and calibration process. OpenTrain gives you the tools to share guidelines, run calibration sessions, and communicate with your team. You can also hire QA leads or adjudicators to resolve disagreements, maintain gold tasks, and monitor quality over time.
Raters work directly in your stack. This includes Argilla, Label Studio, or your own internal preference UI. OpenTrain is tool-agnostic, so you invite hires to your platform and maintain full control over access, data, and security.
Pricing is set between you and the raters you hire. Rates vary based on task complexity, domain expertise required, and volume. You can review proposals, compare rates, and negotiate directly. Payments are handled through OpenTrain with funds released upon your approval.
Yes. For large or ongoing preference labeling projects, OpenTrain can handle recruiting, onboarding, calibration, quality management, and delivery end-to-end. You get a dedicated team working inside your tools without the operational overhead.