Elizabeth M.

Key Skills

Software

Micro1

Other

Top Subject Matter

AI training data labeling quality assurance (text/image/video)

Multi-modal data annotation (image/text/video) and guideline-driven QA

Legal Services & Contract Review

Top Data Types

Text

Image

Document

Top Task Types

Classification

Object Detection

Text Generation

Text Summarization

Transcription

Freelancer Overview

AI Trainer, Micro1 (Remote) — May 2026 to Present. Brings professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Micro1 and Other. Education includes Bachelor of Education, University of Benin (2023). AI-training focus includes data types such as Text and Image and labeling workflows including Classification.

Labeling Experience

Data Annotation Specialist, Atlas Capture (Remote) — February 2026 to Present

OtherImageClassification

As a Data Annotation Specialist at Atlas Capture, you improved annotation accuracy by implementing structured guideline refinement. You completed large volumes of annotations across image, text, and video datasets while maintaining attention to detail. You applied labeling guidelines consistently to reduce inconsistencies and support higher-quality review outcomes. • Completed 1000+ annotations across image/text/video datasets • Refined annotation guidelines to reach ~98% accuracy • Maintained quality while meeting weekly labeling targets • Participated in quality reviews and used feedback to improve

2026 - Present

AI Trainer, Micro1 (Remote) — May 2026 to Present

Micro1TextClassification

As an AI Trainer at Micro1, you worked to improve AI training data quality through accurate labeling and quality assurance. You performed annotation validation and checks to ensure consistency and improve dataset reliability for downstream model performance. You also identified annotation inconsistencies and corrected them during audits and evaluations. • Improved annotation accuracy across text, image, and video datasets • Performed labeling validation and QA during training/evaluation • Audited data for top quality scores and project evaluation success • Corrected inconsistencies to improve reliability and model performance

2026 - Present

Education

Work History