Video Annotator
Classifying, identifying, rating, and evaluating all generalist types of video prompts provided and working to provide fine-tuned feedback to improve the product.
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Over the past few years, I have specialized in data labeling to support AI development, with a focus on text and document annotation but a broader set of experiences across image, text, audio and video labeling. Using internal tools, I processed and labeled government documents—classifying forms, extracting key data points, and validating OCR results to train natural language processing models. My communications background helped me maintain high accuracy in identifying context-sensitive information, such as named entities and document intent. I also contributed to refining annotation guidelines and improving workflow clarity across multilingual datasets. More broadly speaking, I have comprehensive experience with efficiently and effectively rating, refining, and identifying massive sets of image, text, audio, and video data sets by acting as a generalist AI trainer.
Classifying, identifying, rating, and evaluating all generalist types of video prompts provided and working to provide fine-tuned feedback to improve the product.
Various generalist projects transcribing, identifying, and labeling the tone/emotion of audio recordings provided.
Summarizing, rating and evaluating, translating, and writing responses, contextualizations, and justifications for a generalist variety of prompts on topics from politics to economics to arithmetic.
Various ongoing projects & prompts regarding classifying, evaluating, and penning prompts and responses for images provided and requested.
For private political clients: document classification, text summarization, data analysis, NER, redaction labeling.
Bachelor of Arts, Politics & Business of Entertainment, Media & Technology
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