Johnston T.

Key Skills

Software

Don't disclose

Label Studio

Top Subject Matter

Large language models and English linguistic QA/evaluation

Natural language processing

conversational AI annotation

Top Data Types

Text

Audio

Document

Top Task Types

Classification

Freelancer Overview

Senior AI Data Specialist | OpenAI Projects (Remote). Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Label Studio. Education includes Bachelor of Arts, North Carolina State University (2018). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Senior AI Data Specialist | OpenAI Projects (Remote)

Don't discloseText

Evaluated and refined AI-generated English content for accuracy, readability, cultural nuance, and guideline compliance. Reviewed linguistic data and provided targeted feedback to improve LLM prompt understanding and response quality. Built and maintained evaluation rubrics to consistently measure AI output quality improvements. • Assessed responses for factual accuracy, tone, coherence, and compliance. • Conducted linguistic data reviews and iterative refinements for prompt optimization. • Collaborated with engineering teams to improve training datasets for chatbots and generative AI. • Ensured ethical and unbiased AI content development using established tools and guidelines.

2020 - Present

AI Data Annotator | Linguadata Solutions (Raleigh, NC)

Label StudioTextClassification

Performed text and dialogue annotation to support NLP and conversational AI model training. Reviewed large English datasets to identify errors and improve model comprehension, while ensuring consistent categorization of intent, sentiment, and contextual meaning. Supported speech recognition and language generation through linguistic QA testing. • Annotated conversational text and dialogue for NLP/NLU training. • Checked dataset consistency and precision across intent, sentiment, and context labels. • Conducted linguistic QA to improve downstream speech recognition and language generation. • Flagged errors to enhance dataset quality for conversational AI models.

2018 - 2020

Education

Work History