Artificial Intelligence Trainers

When working on a training project, AI trainers organize, label, and clean large data sets (e.g., text, images, audio) of both unstructured and structured data and create structured input-output pairs that teach AI models how to interpret prompts. They do so to train the AI model to recognize inputs and identify patterns to meet a specific goal (such as teaching a chatbot to understand customer inquiries and interact effectively with a human or training an AI model to detect cancer from x-rays or MRIs).

AI trainers verify the accuracy of AI outputs and flag those that are inaccurate, biased, discriminatory, or are otherwise in error. They fine-tune models to ensure that outputs are accurate, on subject, and non-biased. For example, if an AI trainer is teaching an AI model to identify photos of lions, but the AI output also shows images of tigers and cats, the trainer must adjust and retrain the model to omit images of unwanted felines. AI trainers also stress-test systems for robustness and accuracy to ensure consistent performance. They continue to improve AI models based on their review of AI outputs and customer feedback.

AI trainers work closely with data scientists and analysts, machine learning engineers, developers, subject-area experts, and other types of workers to ensure that the AI models that are being trained or improved align with organizational objectives.