Amalia G.

I am an experienced AI Trainer and data annotation specialist specializing in reviewing, auditing, and refining AI models. My core expertise is identifying AI slop, including artifacts, anatomical errors, structural inconsistencies and prompt-adherence failures. I have 6 years of experience annotating and labeling various data types, including images, videos, and point clouds, using the Computer Vision Annotation Tool (CVAT) and applying computer vision concepts and terminology to complex edge cases. I have exceptional attention to detail, documentation discipline, and the ability to collaborate with data scientists, machine learning engineers, and project managers to meet deadlines and high project standards. I possess strong interpersonal and communication skills, adaptability, and resilience in dynamic, fast-paced environments My goal is to ensure the next generation of AI tools isn't just powerful, but intuitive, accessible, and aligned with human needs. By combining deep UI/UX expertise with rigorous AI evaluation, I help models master layout logic, visual communication, and intuitive decision-making.