I help businesses and AI teams improve content quality, accuracy, and performance through a combination of data annotation, localization, and content optimization.

I have a strong background in health-related content analysis, linguistic validation, and AI model evaluation. I specialize in annotating, reviewing, and validating both structured and unstructured data, including medical texts, AI-generated responses, and domain-specific content.

My core expertise includes:
• Medical and healthcare data annotation (clinical texts, patient-facing materials, AI-generated medical content)
• LLM evaluation and RLHF-style feedback
• Fact-checking and hallucination detection in health-related outputs
• Linguistic validation and terminology consistency (EN–PT)
• Quality assurance and guideline-based labeling
• Sensitive content identification and regulatory awareness

In addition, I support businesses by improving ad and website content through localization and optimization, ensuring messages are not only accurate but also clear and effective for the target audience.

I bring a strong analytical mindset, high attention to detail, and a deep focus on accuracy—especially when working with medical terminology, clinical relevance, and user safety.

Fluent in European Portuguese (C2) and Advanced English (C1), I work efficiently in remote environments, following structured workflows and complex annotation guidelines.

If you are looking for reliable, high-quality support in AI training, data annotation, or content optimization, I am ready to contribute.