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Luis
AI Training & Evaluation Specialist with 6+ years in AI & Data Annotation
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Competencias
Specializes in assessing and improving AI system outputs for accuracy and reliability.
Experienced in labeling and reviewing datasets for machine learning, ensuring adherence to strict guidelines.
Ensures high standards in data and AI output quality through detailed review processes.
Works effectively with AI developers and data scientists to enhance training and evaluation workflows.
Educacion
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Resumen
Dedicated AI Training & Evaluation Specialist with over 6 years of experience refining AI models and curating datasets. Skilled in improving model accuracy and reliability for diverse applications.
Logros Clave
- Refined AI language models to improve output clarity and accuracy across text and visual tasks.
- Evaluated and curated large datasets, ensuring high-quality annotations for machine learning applications.
- Collaborated with cross-functional teams to optimize AI training processes and enhance model performance.
Experiencia
AI Training & Evaluation Specialist
Collaborate with AI systems and large language models to refine outputs for clarity, accuracy, and reliability across text and visual-related tasks.. Evaluate image-based and contextual AI outputs using structured guidelines and quality standards.. Apply careful observation and analytical reasoning to identify inconsistencies, hallucinations, or safety concerns in AI responses.. Conduct web research to verify information and support accurate AI-generated outputs.. Design and iterate prompts to improve AI reasoning, visual interpretation, and task completion quality.. Provide structured feedback and evaluations to improve AI training datasets and model performance.
Data Annotation & Content Quality Analyst
Labeled, reviewed, and curated datasets for machine learning applications, including text and visual content classification tasks.. Applied detailed project guidelines to ensure annotation accuracy, consistency, and compliance with quality standards.. Ranked and compared AI outputs based on relevance, accuracy, and adherence to task instructions.. Maintained strong attention to detail while completing high-volume annotation and evaluation tasks.. Contributed to improving AI model performance through systematic data review and structured evaluation.