Beth M.

Key Skills

Software

Appen

CloudFactory

CrowdSource

Labelbox

Micro1

OneForma

Remotasks

Surge AI

Telus

Top Subject Matter

AI training data annotation

prompt evaluation

and content quality

Top Data Types

Text

Image

Video

Top Task Types

Classification

Freelancer Overview

AI Trainer & Data Annotator | Atlas (Remote). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N and A. Education includes Higher Diploma, Kenya Medical Training College (KMTC) and Higher Diploma, Zetech University. AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Data Labeler & Data Annotator | Outlier AI (Remote)

Text

Provided AI training and data annotation support focused on text evaluation and labeling tasks. Reviewed AI-generated outputs to identify inaccuracies and support model improvement efforts. Demonstrated consistent accuracy and attention to detail while collaborating within established project guidelines. • Evaluated AI-generated text outputs • Labeled text data for training workflows • Identified inaccuracies for model updates • Followed project guidelines to deliver quality outputs

2025 - Present

AI Data Labeler & Data Annotator | Handshake AI (Remote)

TextClassification

Worked as an AI Data Labeler and Data Annotator on machine learning projects by categorizing, tagging, and reviewing datasets. Maintained high-quality standards while completing text and content evaluation tasks aligned to annotation guidelines. Met productivity targets and ensured labeled outputs supported improved model accuracy. • Categorized and tagged dataset items • Conducted text/content evaluation per instructions • Ensured guideline compliance and labeling accuracy • Achieved productivity targets while maintaining quality

2025 - Present

AI Trainer & Data Annotator | Atlas (Remote)

Text

Served as an AI Trainer and Data Annotator by reviewing and evaluating AI-generated responses for accuracy, relevance, and safety. Performed data annotation and data labeling to support AI model improvement projects while strictly following project guidelines and quality standards. Classified, tagged, and organized datasets with attention to detail, providing feedback on inconsistencies to enhance language model outputs. • Reviewed AI outputs for correctness and safety compliance • Labeled and annotated dataset entries for training and QA • Followed detailed guidelines and maintained confidentiality • Reported issues and feedback to improve model performance

2025 - Present

Education

Work History