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Scale AI
AppenNo subject matter listed
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AudioI am an AI/LLM data specialist with over two years of hands-on experience creating, annotating, and evaluating high-quality English conversational datasets for large language model training. My expertise spans response quality scoring, safety and coherence assessment, RLHF support, and prompt engineering, with a strong focus on producing clean, natural, and contextually accurate data. I have worked extensively on platforms such as Outlier, Scale AI, Appen, and Remotasks, consistently delivering precise results and maintaining top-tier accuracy metrics across high-volume projects. My background also includes technical communication in Web3 and cybersecurity domains, enabling me to generate and evaluate AI training data in both general and highly technical contexts. I am reliable, adaptable, and thrive in remote, instruction-driven environments where accuracy and consistency are critical.
Recorded clean neutral-accent English audio datasets for speech and conversational AI training. Maintained timing, fluency, and quality standards required by platform QA teams across multiple recording sessions.
Produced structured English conversational datasets for LLM training covering diverse topics, registers, and dialogue contexts. Ensured natural language flow, neutral tone, and contextual soundness aligned with platform QA standards.
Evaluated LLM-generated responses across multiple AI platforms using multi-dimensional rubrics covering accuracy, safety, coherence, helpfulness, and tone. Averaged 50+ evaluations per active project cycle. Flagged edge cases, ambiguous outputs, and safety-critical failures per strict platform guidelines.
Master of Science, Marketing
BSc, Marketing
Blockchain & Web3 Community Contributor
Cybersecurity Specialist
