AI Data Annotation & RLHF (PlanetSpark - Public Speaking Expert)
In this remote freelancing role, I evaluated communication patterns and annotated strengths and weaknesses with detailed written feedback. The position involved designing and delivering lesson frameworks based on learner behaviour analysis, which strongly parallels rubric-based data annotation and RLHF workflows. I maintained consistent, criterion-referenced feedback to uphold accuracy and quality standards vital for high-quality AI training data. • Provided structured annotation and feedback for student responses, analogous to AI evaluation and quality rating tasks. • Applied analytical thinking to judge and classify language, supporting natural language processing (NLP) model training. • Operated independently with reliable async self-management—critical for remote data annotation roles. • Demonstrated attention to detail and accuracy in large-scale student data assessments.