AI Data Annotation & Model Evaluation (Independent/Project Experience)
Annotated and labeled text datasets to support AI training tasks and downstream machine learning use cases. Evaluated AI-generated responses for accuracy, relevance, and guideline adherence to improve dataset quality. Applied prompt engineering methods to refine expected behaviors for more reliable model outputs. • Labeled text inputs according to structured task instructions • Performed quality checks on AI responses against defined criteria • Improved response consistency by iterating on prompts • Followed simulated AI workflow guidelines to ensure dataset fidelity