Project Beet
Played a direct role in improving AI performance across real jobs, real tasks, and real-world decisions.
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I have hands-on experience in data labeling, AI training data evaluation, and quality assurance, particularly through my roles as a Search Quality Rater and AI programming output evaluator. My work involves analyzing large volumes of search results, web pages, and AI-generated content for relevance, accuracy, and adherence to guidelines, as well as identifying issues like factual inaccuracies, misleading information, and spam. I have also contributed to improving AI models by creating and assessing C#/.NET code examples, troubleshooting scenarios, and providing structured feedback to enhance model performance. With a strong technical background in Python, SQL, and cloud tools like Azure, I am adept at data-driven solution design and process optimization. I am passionate about leveraging my analytical skills to ensure high-quality training data and support the development of effective AI systems.
Played a direct role in improving AI performance across real jobs, real tasks, and real-world decisions.
• Evaluated search results, web pages, and AI-generated content for relevance, usefulness, trustworthiness, and guideline adherence, applying consistent judgment across large volumes of tasks • Identified quality issues including misleading content, factual inaccuracies, spam, and poor UX, providing clear, structured feedback to improve ranking and model performance
- Evaluated AI-generated programming outputs for accuracy, efficiency, and best-practice alignment - Analyzed programming prompts to identify logic gaps and edge cases, improving model output quality
Sorted through Instagram pages to select ideal videos for identification and labeling. These were fed into an AI model to produce advertisement keywords.
Bachelor of Science, Computer Science
Business Process Specialist
IT Assistant