Multi-Modal Search Relevance & Content Classification
Evaluated the quality and relevance of image-based search results for a major search engine provider. Tasks involved analyzing user query intent and rating returned visual assets for accuracy, quality, and appropriateness based on a multi-dimensional scoring rubric. Classified hundreds of daily image samples into specific taxonomies to improve content discovery algorithms and reduce visual search errors.