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Gerald A.

Gerald A.

Data Annotation Specialist (Remote) — Data labeling and AI output comparison/evaluation for ML training

USA flagDallas, Usa

Key Skills

Software

Other

Top Subject Matter

Machine learning model training data
AI-generated output evaluation
Data labeling for content tagging and evaluation from multi-source datasets

Top Data Types

ImageImage
AudioAudio
VideoVideo
TextText
DocumentDocument

Top Task Types

ClassificationClassification

Freelancer Overview

Data Annotation Specialist (Remote) — Data labeling and AI output comparison/evaluation for ML training. Core strengths include Other. Education includes Bachelor of Science, The University of Texas at Austin (2023). AI-training focus includes data types such as Image, Audio, and Video and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Data Entry & Research Analyst (Remote) — Content evaluation and tagging with data cleaning/preprocessing

OtherTextTextClassificationClassification

Collected, cleaned, and preprocessed structured and unstructured data from multiple sources to enable business analysis workflows. Evaluated and tagged digital content while adhering to project guidelines and maintaining documentation for traceability. Produced a high volume of annotated data each month while meeting quality accuracy targets. • Data collection and preprocessing (structured/unstructured). • Content evaluation and tagging per project guidelines. • Maintained logs/documentation for reproducible workflows. • Delivered 100+ hours of annotated data monthly with >97% accuracy.

2023 - Present

Data Annotation Specialist (Remote) — Data labeling and AI output comparison/evaluation for ML training

OtherImageImage

Annotated multi-modal datasets (images, audio, and video) to support machine learning model training and downstream evaluation. Performed pairwise comparison tasks to assess AI-generated responses and improve model response quality. Applied quality assurance processes to ensure data integrity and consistent labeling across large datasets. • Image/audio/video labeling for ML training datasets. • Pairwise content comparison to evaluate AI outputs. • QA checks for consistency and integrity across large corpora. • Asynchronous collaboration with remote team members across time zones.

2023 - Present

Education

T

The University of Texas at Austin

Bachelor of Science, Linguistics and Cognitive Science

Bachelor of Science
2019 - 2023

Work History

C

Company not specified

ai data annotation

Location not specified
Not specified