Mariana M.

Key Skills

Software

Other

Top Subject Matter

Linguistics Domain Expertise

AI-generated content

Brazilian Portuguese

Top Data Types

Text

Image

Document

Top Task Types

RLHF

Prompt + Response Writing (SFT)

Classification

Segmentation

Text Generation

Text Summarization

Freelancer Overview

AI Data Evaluator / Annotator | Welocalize. Brings 12+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science, Faculdade de Medicina do ABC (FMABC) (2022) and Bachelor of Science, Federal University of Rio de Janeiro (UFRJ) (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Trainer / Scientific AI Evaluator (Freelance) | Outlier

Text

As an AI Trainer and Scientific AI Evaluator (Freelance) at Outlier, I evaluated and ranked AI-generated STEM responses for reasoning quality, factual accuracy, coherence, and adherence to guidelines. I produced structured written justifications and identified hallucinations, inconsistencies, and linguistic errors in model outputs. My role also included conducting multimodal evaluation tasks involving both text and image interpretation. • Generated prompts and edge cases to test model robustness • Assessed AI-generated STEM content and performed detailed response analysis • Identified and documented logical errors and hallucinations in outputs • Worked with prompt evaluation frameworks and internal tools to perform evaluations.

2026 - Present

AI Data Evaluator / Annotator | Welocalize

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As an AI Data Evaluator and Annotator at Welocalize, I annotated and evaluated large-scale text datasets to enhance AI model performance. My work focused on assessing language quality, cultural appropriateness, and contextual alignment for Brazilian Portuguese content. I produced high-quality annotations by adhering to structured guidelines and performing in-depth fact-checking and research. • Evaluated and annotated AI-generated text for accuracy and coherence • Identified language-related issues, inconsistencies, and edge cases in model outputs • Maintained high annotation productivity and strict quality standards • Utilized internal/proprietary data annotation tools for all tasks.

2026 - Present

Education

Work History