Key Skills

Software

Mercor

Other

Top Subject Matter

Large Language Model (LLM) Evaluation

LLM Evaluation & Annotation

LLM Output Evaluation & Localization

Top Data Types

Text

Image

Top Task Types

Data Collection

Freelancer Overview

Data Annotation Specialist & LLM Evaluator. Core strengths include Mercor, Outlier, and Other. Education includes Doctor of Philosophy, INPE (2017). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Research Participant & Contributor

OtherTextData Collection

As a Research Participant & Contributor on Prolific, I assisted in research studies involving AI evaluation tasks and global data collection. Projects were for academic and technology sector clients, demanding integrity and precision. My work contributed valuable, high-quality datasets to university and industry research initiatives. • Participated in structured data collection protocols. • Completed AI evaluation and annotation activities. • Supported diverse academic and applied research projects. • Edited and submitted labeled data for analysis.

As a Research Participant & Contributor on Prolific, I assisted in research studies involving AI evaluation tasks and global data collection. Projects were for academic and technology sector clients, demanding integrity and precision. My work contributed valuable, high-quality datasets to university and industry research initiatives. • Participated in structured data collection protocols. • Completed AI evaluation and annotation activities. • Supported diverse academic and applied research projects. • Edited and submitted labeled data for analysis.

2026 - Present

AI Data Annotator & LLM Evaluator

Text

Serving as an AI Data Annotator & LLM Evaluator with Outlier, I evaluated and annotated LLM outputs across varied tasks. I was selected for the Oracle Program, highlighting top-tier performance and access to advanced projects. The role involved comprehensive evaluations and high-level contribution to LLM assessment. • Assessed and annotated LLM textual outputs across multiple tasks. • Participated in the Oracle Program for leading contributors. • Provided informed feedback for model optimization. • Ensured accuracy and relevance of annotated data.

Serving as an AI Data Annotator & LLM Evaluator with Outlier, I evaluated and annotated LLM outputs across varied tasks. I was selected for the Oracle Program, highlighting top-tier performance and access to advanced projects. The role involved comprehensive evaluations and high-level contribution to LLM assessment. • Assessed and annotated LLM textual outputs across multiple tasks. • Participated in the Oracle Program for leading contributors. • Provided informed feedback for model optimization. • Ensured accuracy and relevance of annotated data.

2025 - Present

Data Annotation Specialist & LLM Evaluator

MercorText

As a Data Annotation Specialist & LLM Evaluator at Mercor, I compared and ranked AI model responses in RLHF workflows. I identified hallucinations, alignment failures, and reasoning errors, and delivered rubric-based feedback to improve model fine-tuning. The role required meticulous attention to linguistics and model behavior analysis. • Compared and ranked model-generated text responses based on rubric scoring. • Detected and flagged issues such as hallucinations and misalignments. • Contributed to RLHF (Reinforcement Learning from Human Feedback) pipelines. • Synthesized evaluation results to guide model improvement.

As a Data Annotation Specialist & LLM Evaluator at Mercor, I compared and ranked AI model responses in RLHF workflows. I identified hallucinations, alignment failures, and reasoning errors, and delivered rubric-based feedback to improve model fine-tuning. The role required meticulous attention to linguistics and model behavior analysis. • Compared and ranked model-generated text responses based on rubric scoring. • Detected and flagged issues such as hallucinations and misalignments. • Contributed to RLHF (Reinforcement Learning from Human Feedback) pipelines. • Synthesized evaluation results to guide model improvement.

2025 - Present

Search Engine Evaluator

OtherText

As a Search Engine Evaluator at Moravia, I assessed search result relevance and user intent alignment. This was achieved by applying structured rating frameworks, supporting ongoing machine learning model improvement. The position required ongoing evaluation and consistent application of guidelines. • Judged search result relevance for diverse queries. • Evaluated user intent matching with returned links. • Used structured rating frameworks consistently. • Contributed to search model optimization loops.

As a Search Engine Evaluator at Moravia, I assessed search result relevance and user intent alignment. This was achieved by applying structured rating frameworks, supporting ongoing machine learning model improvement. The position required ongoing evaluation and consistent application of guidelines. • Judged search result relevance for diverse queries. • Evaluated user intent matching with returned links. • Used structured rating frameworks consistently. • Contributed to search model optimization loops.

2024 - Present

Data Annotation Specialist & LLM Evaluator

OtherText

At Alignerr, I served as a Data Annotation Specialist & LLM Evaluator, focusing on reasoning quality, factual accuracy, and instruction adherence of LLM outputs. My responsibilities included adversarial prompt testing and localization review between Portuguese and English. The position demanded detailed analysis and robust linguistic understanding. • Evaluated the factual and logical soundness of AI responses. • Performed adversarial prompt testing for robustness checks. • Reviewed localization accuracy for PT-EN translations. • Enhanced model instruction-following capabilities.

At Alignerr, I served as a Data Annotation Specialist & LLM Evaluator, focusing on reasoning quality, factual accuracy, and instruction adherence of LLM outputs. My responsibilities included adversarial prompt testing and localization review between Portuguese and English. The position demanded detailed analysis and robust linguistic understanding. • Evaluated the factual and logical soundness of AI responses. • Performed adversarial prompt testing for robustness checks. • Reviewed localization accuracy for PT-EN translations. • Enhanced model instruction-following capabilities.

2024 - Present

Education

Work History