Kelvin C.

Key Skills

Software

Appen

Scale AI

Snorkel AI

SuperAnnotate

Top Subject Matter

Generative AI prompt and response evaluation

conversational AI datasets

content moderation/safety

Top Data Types

Text

Image

Document

Top Task Types

Classification

Freelancer Overview

AI Data Annotator & AI Training Contributor (Remote). Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Bachelor of Science, University of Texas at Austin. AI-training focus includes data types such as Text and Image and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Data Labeling Specialist (Remote)

Don't discloseImageClassification

Annotated and categorized text, image, and conversational datasets used for machine learning model development. Performed detailed labeling tasks adhering to strict project instructions and quality standards. Supported dataset validation and quality review processes to improve annotation consistency while providing structured classification and feedback for training workflows. • Labeled and categorized images and conversational/text data per guidelines. • Conducted dataset validation and quality review for consistency. • Supported AI training workflows through accurate classification. • Maintained productivity and reliability in remote project environments.

2018 - Present

AI Content Evaluation Specialist (Remote)

Don't discloseText

Evaluated AI-generated content, search engine outputs, and language datasets to improve machine learning performance. Annotated and categorized text datasets for natural language processing and conversational AI systems using detailed labeling guidelines. Conducted quality reviews, identified inconsistencies in large-scale labeling projects, and improved outputs through structured human feedback. • Maintained high accuracy and productivity against labeling targets. • Performed quality checks to detect annotation inconsistencies. • Applied structured feedback to support better model outputs. • Supported dataset improvement for conversational and NLP training.

2018 - Present

AI Search Relevance & Data Analyst (Remote)

Don't discloseText

Conducted search relevance analysis, content evaluation, and AI dataset categorization for machine learning projects. Reviewed AI-generated content and search engine outputs to improve algorithm accuracy and user relevance. Performed quality assurance reviews on annotated datasets and worked with multilingual/conversational data to support NLP systems. • Evaluated search outputs and user-intent alignment. • Ensured compliance with annotation guidelines through QA. • Supported natural language processing dataset categorization. • Collaborated with international project coordinators and QA teams remotely.

2018 - Present

AI Data Analyst & Annotation Specialist (Remote)

Don't discloseTextClassification

Supported AI training operations through text classification, data categorization, content evaluation, and search relevance analysis. Conducted quality assurance reviews on annotated datasets to ensure consistency and compliance with project requirements. Worked with multilingual and conversational datasets to improve machine learning model performance while contributing to throughput and quality improvements. • Performed QA checks on labeled datasets for policy and guideline adherence. • Assisted in process improvements to enhance annotation throughput. • Collaborated remotely with coordinators and quality teams across time zones. • Improved model training outcomes using structured categorization and evaluation workflows.

2018 - Present

AI Prompt Evaluator & Data Specialist (Remote/Distributed)

Don't discloseText

Performed high-volume data annotation, labeling, and validation for large-scale AI model training projects. Evaluated AI-generated responses for quality, factual accuracy, safety, and alignment with established standards. Collaborated with distributed AI operations teams to improve annotation consistency and workflow efficiency while maintaining confidentiality and compliance. • Annotated text and conversational datasets according to detailed guidelines. • Refined prompt-response evaluation frameworks to improve data quality processes. • Supported structured quality improvements across operations teams. • Maintained strict confidentiality while working with sensitive datasets.

2018 - Present

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Education

Work History