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Data annotation specialists add the labels your models learn from: tags and boxes on images, categories on text, transcripts of audio, and ratings of AI answers. On RemoteAI you contact them directly, brief them with your own guidelines, and keep the work in your own tool.
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Data annotation specialists add the labels your models learn from: tags and boxes on images, categories on text, transcripts of audio, and ratings of AI answers. On RemoteAI you contact them directly, brief them with your own guidelines, and keep the work in your own tool.
Annotation specialists label images, video frames, text and audio from your guidelines, check each other's work on a sample, and report accuracy against a gold set you provide. For teams building on large language models, AI training specialists rate and compare model answers, write better ones, and test a model on real tasks (often called RLHF or model evaluation). Good annotators ask questions early, flag unclear cases instead of guessing, and keep your data private.
Finding the right data annotation specialist requires more than evaluating technical skills — it means identifying someone who ships production-ready work and understands your business goals. Here is exactly how to do it.
Define each label, give two or three clear examples, and show the hard cases with the right answer. Unclear guidelines are a common cause of labeling errors.
Label 50 to 100 items yourself. Accuracy on these items tells you whether the work is usable, and timing them tells you the size of the job.
Ask for a few hundred items first and review them before the full job. It is the cheapest moment to fix the guidelines.
Decide who reviews which share of items, and what data the labelers may see. Remove personal data the task does not need.
Cost depends on the size of the project and the seniority you need. These are the three usual project sizes, from smallest to largest: put a budget in your job post and ask candidates for a quote on yours.
Data annotation services add the labels a machine learning model learns from: tags on images, boxes around objects, categories on text, transcripts of audio, or ratings of AI answers. You can use a managed vendor or hire annotation specialists directly and brief them yourself.
It depends on how hard each item is, how many items there are and how much review you ask for. Time yourself on 50 items to estimate the hours, put a budget in your job post, and ask candidates for a quote per item or per hour with the review included. RemoteAI takes no placement fee on what you pay them.
Use a gold set you labeled yourself, review a pilot batch before the full job, and have two people label the same sample to see where they disagree. Ask for an accuracy report against the gold set.
RLHF annotation means people rate or compare answers written by an AI model, or write better ones, so the model learns which answers are preferred. It needs careful readers who follow detailed guidelines, and often subject knowledge such as coding or medicine.
Usually, yes. Ask which labeling tools they have used before and give them an account in yours, which keeps your data and your quality checks in one place.