Barbara Lopes Garcia Van Meter

Key Skills

Software

Appen

Scale AI

Other

Mercor

CrowdSource

Internal/Proprietary Tooling

Top Subject Matter

Multimedia Data Annotation

Large Language Models (LLM) Training

AI/ML Training Data

Top Data Types

Image

Text

Video

Document

Top Task Types

Classification

Bounding Box

Segmentation

Entity (NER) Classification

Object Detection

Text Generation

Question Answering

Text Summarization

RLHF

Evaluation/Rating

Data Collection

Freelancer Overview

Detail-oriented data professional with 5+ years of experience in AI/ML data annotation and LLM evaluation, processing 150+ multimedia items daily with 98–100% accuracy in both English and Portuguese. Skilled at evaluating LLM outputs, reviewing datasets for quality, and collaborating with cross-functional teams to enhance AI model performance. Background in financial operations (6+ years) provides a strong foundation in data integrity and process improvement. Currently pursuing a Bachelor's in Business Management.

Labeling Experience

Data Annotation Specialist

MercorVideoQuestion Answering

As a Data Annotation Specialist at Mercor, I worked on multiple AI/ML projects involving classification, relevance evaluation, and identification labeling. My responsibilities included executing guideline-driven annotation and conducting thorough quality reviews. I focused on ensuring high consistency and excellence in labeled data outputs. • Engaged in cross-functional team collaboration for quality assurance • Maintained high standards in data integrity and accuracy • Supported diverse annotation projects concurrently

As a Data Annotation Specialist at Mercor, I worked on multiple AI/ML projects involving classification, relevance evaluation, and identification labeling. My responsibilities included executing guideline-driven annotation and conducting thorough quality reviews. I focused on ensuring high consistency and excellence in labeled data outputs. • Engaged in cross-functional team collaboration for quality assurance • Maintained high standards in data integrity and accuracy • Supported diverse annotation projects concurrently

2026 - Present

AI Training Specialist

Scale AITextRLHF

As an AI Training Specialist at Outlier (Scale AI), I evaluated LLM outputs for accuracy, coherence, and safety. I generated prompts, assessed responses, and provided detailed feedback to improve language model performance. Additionally, I contributed to content quality assessment and response rewriting. • Applied preference ranking and rubric-based evaluations for LLM training • Generated and curated prompts to enhance dataset quality • Engaged in iterative evaluation cycles to refine model outputs • Ensured guideline compliance for all LLM-related data tasks

As an AI Training Specialist at Outlier (Scale AI), I evaluated LLM outputs for accuracy, coherence, and safety. I generated prompts, assessed responses, and provided detailed feedback to improve language model performance. Additionally, I contributed to content quality assessment and response rewriting. • Applied preference ranking and rubric-based evaluations for LLM training • Generated and curated prompts to enhance dataset quality • Engaged in iterative evaluation cycles to refine model outputs • Ensured guideline compliance for all LLM-related data tasks

2024 - Present

AI Training Data Specialist

OtherImageBounding Box

At RWS Global, I served as an AI Training Data Specialist, annotating, contextualizing, and refining large-scale text datasets. I performed preference ranking and applied data augmentation techniques to diversify and strengthen training data. My role focused on enhancing model reasoning and dataset integrity. • Labeled and analyzed element-level dataset components • Applied quality review standards before submission • Collaborated on labeling approaches for diverse AI/ML projects • Contributed to iterative dataset improvement

At RWS Global, I served as an AI Training Data Specialist, annotating, contextualizing, and refining large-scale text datasets. I performed preference ranking and applied data augmentation techniques to diversify and strengthen training data. My role focused on enhancing model reasoning and dataset integrity. • Labeled and analyzed element-level dataset components • Applied quality review standards before submission • Collaborated on labeling approaches for diverse AI/ML projects • Contributed to iterative dataset improvement

2026 - 2026

Data Annotator

AppenImageClassification

As a Data Annotator at Appen Butler Hill, I annotated and reviewed a high volume of multimedia content in both English and Portuguese. My work focused on content classification, relevance evaluation, and identification labeling using established guidelines. I ensured a sustained accuracy rate of 98–100% throughout my tenure. • Reviewed and labeled over 150 images, videos, and text items daily • Collaborated with global annotation teams to maintain label consistency • Utilized platform tools for large-scale annotation assignments • Excelled in multilingual environments to support diverse data projects

As a Data Annotator at Appen Butler Hill, I annotated and reviewed a high volume of multimedia content in both English and Portuguese. My work focused on content classification, relevance evaluation, and identification labeling using established guidelines. I ensured a sustained accuracy rate of 98–100% throughout my tenure. • Reviewed and labeled over 150 images, videos, and text items daily • Collaborated with global annotation teams to maintain label consistency • Utilized platform tools for large-scale annotation assignments • Excelled in multilingual environments to support diverse data projects

2020 - 2026

Education

Work History