AI Image Quality & Instructor
Evaluated and optimized multimodal AI models on Project Aether via Outlier, focusing on image-to-text alignment and visual quality assurance. Key responsibilities included: • Conducting rigorous quality control to identify and filter out visual anomalies, rendering errors, and characteristic "AI slop/artifacts." • Assessing whether model-generated images precisely adhered to complex, multi-layered user prompt instructions. • Evaluating image-to-image consistency and ensuring high-fidelity visual alignment with source criteria. • Providing detailed, objective feedback and data tagging to refine the realism and accuracy of generative AI image models.