Sean D.

Key Skills

Software

Mercor

Data Annotation Tech

Appen

CloudFactory

Google Cloud Vertex AI

iMerit

Labelbox

Label Studio

Micro1

Mindrift

OneForma

Remotasks

Scale AI

Snorkel AI

SuperAnnotate

Surge AI

Toloka

Telus

Top Subject Matter

Generalist topics

English language

Language comprehension and generation

Top Data Types

Text

Image

Audio

Top Task Types

Text Generation

Bounding Box

Segmentation

Classification

Object Detection

Text Summarization

RLHF

Fine-tuning

Red Teaming

Transcription

Computer Programming/Coding

Evaluation/Rating

Freelancer Overview

AI Training Specialist. Core strengths include Mercor and Data Annotation Tech. Education includes Bachelor of Arts, Arizona State University (2023) and Diploma, Maricopa Community Colleges (2025). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Text Generation.

Labeling Experience

AI Training Specialist

MercorTextTranscription

As an AI Training Specialist at Mercor AI, I evaluated and refined AI-generated English content for grammar, clarity, and adherence to instructions across multiple formats. I developed writing prompts and tone guidelines to enhance LLM outputs and provided detailed feedback on model quality. My work included large-scale response evaluation and preference ranking to directly improve language model accuracy and functionality. • Reviewed and edited diverse AI-generated texts for style, factuality, and grammatical correctness. • Authored 500+ writing prompts and tone/parameter guidelines for language model tasks. • Assessed over 10,000 response pairs for accuracy, clarity, and natural English usage. • Contributed to pipelines reducing model error rates and maintained a performance quality score above 87%.

2025 - 2026

Data Annotation Specialist

Data Annotation TechTextText Generation

During my time as a Data Annotation Specialist at DataAnnotation.Tech, I annotated, analyzed, and corrected vast volumes of text data for AI language modeling. I evaluated AI-generated output for naturalness and linguistic accuracy and corrected inconsistencies to improve dataset reliability. My work supported complex classification, annotation, and editorial standards in AI model training. • Annotated and quality-checked over 50,000 textual data points for language model improvement. • Evaluated and edited AI outputs for grammar, coherence, and human-like writing standards. • Achieved an 89% inter-annotator agreement score on difficult classification assignments. • Applied consistent linguistic, editorial, and factual correction to diverse text tasks.

2023 - 2025

Education

Work History