Charles E.

Key Skills

Software

Label Studio

Other

CVAT

Top Subject Matter

Multilingual NLP training data for chatbots and RLHF fine-tuning (English/Yoruba/French)

Healthcare triage chatbot datasets and intent classification labeling (Yoruba)

Top Data Types

Text

Top Task Types

Fine-tuning

RLHF

Classification

Freelancer Overview

AI Assistant Developer / Data Operations Specialist — PulseMind Technologies Ltd. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, Other, and CVAT. Education includes Bachelor of Engineering, Federal University of Technology Minna (2021) and Certification, AI+ Training Africa (2022). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning, RLHF, and Fine Tuning.

Labeling Experience

AI Assistant Developer / Data Operations Specialist — PulseMind Technologies Ltd

Label StudioTextFine-tuningRLHF

Led a team of annotators to produce training data for multilingual chatbot models in English, Yoruba, and French. Worked on data collection and RLHF-oriented cycles by generating preference and evaluation signals from model outputs. Coordinated iterative feedback loops with engineering to improve fine-tuning outcomes for customer-facing AI assistants. • Used Label Studio and ScaleAI to manage and produce training labels • Produced/curated RLHF data to reduce response error rates via iterative prompt refinement • Designed evaluation scoring for relevance, safety, and tone feeding results into fine-tuning cycles • Supported LangChain-based agentic workflows and RAG-related datasets for improved tool-use responses

2023 - Present

AI Research Intern - AfriTech AI Research Hub

CVATTextClassification

Supported supervised fine-tuning work by preprocessing and cleaning NLP datasets for healthcare triage chatbots. Assisted with chatbot dialogue design and intent-labeling for Yoruba-language health queries. Conducted quality assurance reviews on model outputs and documented edge cases for researchers to address. • Cleaned and prepared datasets for NLP model training workflows • Helped design conversational flows and intent classification tasks • Performed QA checks on model outputs and flagged edge cases • Collaborated with researchers to validate results and improve data quality

2020 - 2020

AI Training Intern — AfriTech AI Research Hub

OtherTextFine-tuning

Preprocessed and cleaned datasets for supervised fine-tuning of NLP models used in healthcare triage chatbots. Assisted with dialogue design and intent classification labeling for Yoruba-language health queries. Performed QA on model outputs and flagged edge cases for researcher review. • Cleaned and prepared supervised fine-tuning datasets for medical triage chatbot use • Labeled intent classes within Yoruba-language chatbot dialogues • Conducted quality assurance reviews on chatbot responses and outputs • Reported edge cases to researchers for further iteration

2020 - 2020

Education

Work History