Ikechukwu E.

Key Skills

Software

Label Studio

Scale AI

Appen

Clickworker

AWS SageMaker

Data Annotation Tech

Dataloop

Datumbox

Google Cloud Vertex AI

Img Lab

Labelbox

Lionbridge

LightTag

Mercor

Mindrift

OneForma

Remotasks

SuperAnnotate

Telus

Top Subject Matter

Natural Language Processing

Llms Domain Expertise

Rlhf Domain Expertise

Top Data Types

Text

Image

Document

Top Task Types

Data Collection

Classification

Object Detection

Evaluation/Rating

Transcription

Prompt + Response Writing (SFT)

Fine-tuning

Text Summarization

Question Answering

Bounding Box

Freelancer Overview

With over five years of experience creating AI training data and labeling, I am well-versed in creating multilingual NLP datasets as well as evaluating large language models (LLMs). I have successfully managed multiple annotation projects on platforms such as Toloka, Scale AI, and Appen while producing an average of 98-99% quality compliance through continuous improvement of inter-rater consistency via defined guidelines and grading rubrics. The scope of my work includes annotation, quality assurance (QA) auditing, reinforcement learning from human feedback (RLHF) evaluation, and bias detection, with an emphasis on ensuring cultural and linguistic accuracy in English, Igbo, Yoruba, Hausa, Spanish, and French. My unique capability lies in blending both linguistic knowledge and technical automation to create and improve upon large-scale datasets using various formats (such as JSON, CSV, and XML) and Python-based validation pipelines that improved annotation efficiency by 40%. Additionally, I have assisted in mentoring annotators, leading multilingual QA initiatives, and supporting AI alignment efforts. Through my background in backend development, various data science certifications, and hands-on experience in web scraping and data structuring, I provide both strategic direction as well as technical delivery within AI training workflows.

Labeling Experience

Senior AI Training & Data Annotation Specialist

TolokaText

Led multilingual annotation and QA workflows for NLP and LLM data labeling across five languages. Designed and maintained grading rubrics for LLM response evaluation and contributed to RLHF model alignment. Automated validation to boost annotation throughput and guideline compliance rates. • Supported bias detection and multilingual quality assurance. • Mentored junior annotators on best labeling practices. • Implemented structured quality audits per evaluation cycle. • Enhanced compliance to annotation guidelines by automating workflows.

2022 - Present

Freelance Multilingual AI & Data Annotation Lead

Label StudioTextData Collection

Provided dataset creation, annotation, and QA for low-resource African languages in diverse AI and NLP projects. Managed data gathering, cleaning, and structuring into machine-readable formats for model training. Executed translation validation and localization review for AI systems serving African markets. • Built and annotated large-scale datasets with focus on low-resource languages. • Integrated labeled data with cloud databases and API pipelines. • Automated data pre-processing and cleaning scripts. • Delivered consulting and leadership for multiple research clients.

2018 - Present

AI Model Evaluation & Data Rater

Scale AIText

Rated, annotated, and evaluated AI-generated responses for large-scale NLP and computer vision projects. Implemented labeling frameworks to optimize model training and performance in multiple languages. Contributed feedback for bias, linguistic quality, and data selection protocols. • Annotated both text and image datasets for supervised learning. • Conducted detailed QA and linguistic reviews. • Recommended dataset improvements and bias corrections. • Ensured culturally aligned model outputs.

2017 - 2020

Multilingual Language Translator & Dataset Specialist

Text

Validated and prepared multilingual NLP training datasets for linguistic consistency and contextual accuracy. Delivered professional translation and QA for annotated corpora in multiple languages. Supported data annotation for cross-border language model deployment. • Checked translation accuracy and quality in annotated datasets. • Assisted in developing resources for AI language models. • Maintained data standards for multilingual NLP corpora. • Coordinated with technical teams for model integration.

2013 - 2015

Junior Data Annotation Specialist

AppenTextClassification

Performed structured annotation and classification on search engine and speech recognition datasets. Ensured task accuracy benchmarks while achieving short-term productivity targets. Supported initial dataset development for machine learning systems. • Labeled audio and text data for supervised ML applications. • Adhered to detailed annotation protocols. • Reviewed outputs for accuracy and completeness. • Worked within remote, distributed annotation teams.

2012 - 2013

Education

Work History