Ekemini Christopher

Key Skills

Software

LabelImg

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Entity Ner Classification

Classification

RLHF

Data Collection

Transcription

Freelancer Overview

I have hands on experience working with data labeling and AI training data across text, image, and classification tasks. My work has involved annotating datasets for natural language processing, content moderation, and computer vision projects, ensuring accuracy, consistency, and adherence to detailed guidelines. I’ve worked with structured and unstructured data, handled edge cases carefully, and maintained high quality control standards to improve model performance. I’m comfortable using annotation tools, following complex labeling taxonomies, and meeting tight deadlines without compromising precision. What sets me apart is my attention to detail and strong analytical mindset. I don’t just label data mechanically, I take time to understand the intent behind each task, which helps maintain consistency and reduce ambiguity. My background in tech also helps me understand how labeled data directly impacts model training and evaluation. I’m reliable, quick to adapt to new guidelines, and committed to delivering clean, high-quality datasets that teams can confidently build on.

Labeling Experience

AI Training Data Annotation for NLP & Content Classification

LabelimgTextEntity Ner ClassificationClassification

Worked on multiple AI training data projects focused on text annotation for large language models. Responsibilities included labeling and classifying text data for intent, sentiment, policy compliance, and relevance. Performed Named Entity Recognition (NER), response quality evaluation, and RLHF-style ranking to improve model alignment and accuracy. The project involved annotating thousands of data points while strictly following evolving guidelines and handling complex edge cases. Quality was maintained through consistency checks, peer reviews, and adherence to high accuracy thresholds.

Worked on multiple AI training data projects focused on text annotation for large language models. Responsibilities included labeling and classifying text data for intent, sentiment, policy compliance, and relevance. Performed Named Entity Recognition (NER), response quality evaluation, and RLHF-style ranking to improve model alignment and accuracy. The project involved annotating thousands of data points while strictly following evolving guidelines and handling complex edge cases. Quality was maintained through consistency checks, peer reviews, and adherence to high accuracy thresholds.

2025 - 2025

Education

Work History