Ifeoma O.

Key Skills

Software

Appen

OneForma

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Audio Recording

Bounding Box

Data Collection

Evaluation/Rating

Mapping

Freelancer Overview

I am an experienced AI Training and Data Labeling contributor with hands-on experience across multiple global platforms, including Outlier, Appen, and OneForma. I have worked on a range of projects focused on improving large language models through high-quality human feedback, prompt evaluation, instruction-following assessment, and content accuracy review. My work has involved carefully analyzing AI-generated responses for relevance, clarity, reasoning quality, safety, and guideline compliance. My background is Mathematics and Data Science. I bring strong attention to detail, excellent written communication skills, and the ability to follow complex annotation guidelines consistently. With a background in analytical thinking and content evaluation, I am particularly skilled at identifying subtle errors, bias, tone issues, and logical gaps in AI outputs. I adapt quickly to new tools and workflows and consistently deliver accurate, reliable annotations that help improve model performance and user experience.

Labeling Experience

LLM Evaluation & Human Feedback for AI Training

Scale AITextBounding BoxRelationship

Contributed to multiple AI training projects focused on improving large language model performance through high-quality human feedback. Responsibilities included evaluating AI-generated responses for accuracy, reasoning, relevance, tone, and instruction adherence. Provided structured ratings and written feedback aligned with detailed project guidelines to support RLHF and supervised fine-tuning workflows. Worked on prompt–response analysis, identifying logical errors, hallucinations, bias, and safety issues, and suggesting improved responses where required. Also participated in red-teaming style tasks to test model robustness and safe behavior. Demonstrated strong attention to detail, consistency across annotations, and the ability to adapt quickly to evolving task requirements and annotation standards.

2024

Education

Work History