Joshuah D.

Key Skills

Software

CVAT

Other

Top Subject Matter

AI response evaluation

Computer vision / object detection

NLP / sentiment and entity recognition

Top Data Types

Text

Image

Document

Top Task Types

Bounding Box

Freelancer Overview

AI Response Evaluation Project. Core strengths include N, A, and CVAT. Education includes Bachelor of Science, Florida Atlantic University and Certificate, Coursera. AI-training focus includes data types such as Text and Image and labeling workflows including Evaluation, Rating, and Bounding Box.

Labeling Experience

AI Data Annotation Specialist (Remote)

CVATText

Annotated and evaluated large-scale text and image datasets for AI model training. Applied detailed annotation guidelines to ensure consistent and accurate labels across projects. Conducted quality assurance checks to identify and correct labeling inconsistencies, maintaining high accuracy. • Followed complex guideline sets for label consistency • Performed comparative evaluation of AI-generated responses • Completed tasks under strict deadlines • Adapted to updated annotation standards

2024 - 2025

Natural Language Processing (NLP) Annotation Project

OtherText

Annotated text for natural language processing tasks including sentiment analysis and entity recognition. Labeled linguistic patterns to enable downstream AI training and improve model understanding. Maintained consistency in subjective labeling according to provided guidelines. • Labeled sentiment categories • Identified and tagged named entities for NER • Categorized linguistic patterns • Ensured guideline-compliant, consistent outputs

2024 - 2025

Large-Scale Image Annotation Project

CVATImageBounding Box

Performed large-scale image annotation for object detection tasks using bounding boxes and classification labels. Ensured consistent labeling across a high-volume dataset following a strict taxonomy. Supported AI model training by maintaining compliance with annotation rules. • Labeled 1,000+ images using bounding boxes • Applied classification labels for objects • Followed object detection taxonomy and rules • Maintained dataset consistency for training

2024 - 2025

AI Response Evaluation Project

Text

Evaluated AI-generated outputs for accuracy, relevance, and clarity to support model quality improvements. Provided structured feedback by identifying inconsistencies across ranked responses. Applied critical thinking to compare responses and support selection decisions. • Assessed response quality against guidelines • Ranked and compared multiple AI outputs • Flagged issues and provided improvement notes • Focused on relevance and clarity metrics

2024 - 2025

Education