Data Labeling
The users were not familiar with the project; we were only supposed to do what we were told, but it is easy to guess that the goal was to improve a given AI model.
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I am a detail-oriented and reliable AI content evaluator and data annotation specialist with hands-on experience in reviewing both visual and text-based outputs generated by AI systems. My background includes evaluating AI-generated content against established quality standards and rubrics, providing structured feedback, and consistently applying guidelines to improve model outputs. I am skilled in human-in-the-loop workflows, image and visual content assessment, and quality assurance methodologies, particularly within the context of generative AI models such as text-to-image and image generation. I thrive in fast-paced, research-driven environments, adapt quickly to evolving criteria, and am committed to maintaining high accuracy and confidentiality while collaborating remotely with distributed teams. My passion for emerging technologies and AI ethics, combined with strong attention to detail and pattern recognition, enables me to contribute effectively to machine learning development and data labeling projects.
The users were not familiar with the project; we were only supposed to do what we were told, but it is easy to guess that the goal was to improve a given AI model.
Vocational Diploma, Information Technology
Primary School Diploma, General Education
Animal care and economic welfare.