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Ofana Nelson

Ofana Nelson

AI Training & Data Annotation Specialist

Nigeria flagN/A, Nigeria
Intermediate

Key Skills

Software

No software listed

Top Subject Matter

Large Language Models (LLMs)
Model Alignment
Safety Evaluation

Top Data Types

TextText
ImageImage

Top Task Types

RLHFRLHF
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
Fine-tuningFine-tuning

Freelancer Overview

AI Training & Data Annotation Specialist. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Doctor of Pharmacy, University of Calabar (2024). AI-training focus includes data types such as Text and labeling workflows including RLHF, Prompt + Response Writing (SFT), and Evaluation.

Intermediate

Labeling Experience

High-Volume Structured Dataset Creation (Project)

TextFine Tuning
For High-Volume Structured Dataset Creation projects, I was responsible for producing a high-quality, 30,000+ word narrative-aligned dataset with consistent logical structure for fine-tuning language models. The project involved curating and synthesizing long-form text data with strict adherence to logical and narrative guidelines. Datasets were developed to maximize LLM fine-tuning performance in structured generation tasks. • Built multi-thousand word datasets for LLM training. • Ensured logical consistency across all dataset entries. • Applied narrative alignment principles in data curation. • Supported fine-tuning benchmarks with quality data sets.

For High-Volume Structured Dataset Creation projects, I was responsible for producing a high-quality, 30,000+ word narrative-aligned dataset with consistent logical structure for fine-tuning language models. The project involved curating and synthesizing long-form text data with strict adherence to logical and narrative guidelines. Datasets were developed to maximize LLM fine-tuning performance in structured generation tasks. • Built multi-thousand word datasets for LLM training. • Ensured logical consistency across all dataset entries. • Applied narrative alignment principles in data curation. • Supported fine-tuning benchmarks with quality data sets.

2024 - Present

AI Model Evaluation & Alignment (Project)

Text
Through my role in AI Model Evaluation & Alignment projects, I developed structured criteria to consistently rank and rate AI model outputs, bridging logic gaps and improving overall response reliability. My process used logical frameworks and alignment best practices to benchmark model accuracy. The experience involved crafting and applying detailed evaluation rubrics tailored to LLM alignment and trustworthiness. • Designed evaluation rubrics for LLM output assessment. • Benchmarked AI model responses on safety and consistency. • Addressed logical reasoning gaps through targeted feedback. • Enhanced response reliability via systematic criteria development.

Through my role in AI Model Evaluation & Alignment projects, I developed structured criteria to consistently rank and rate AI model outputs, bridging logic gaps and improving overall response reliability. My process used logical frameworks and alignment best practices to benchmark model accuracy. The experience involved crafting and applying detailed evaluation rubrics tailored to LLM alignment and trustworthiness. • Designed evaluation rubrics for LLM output assessment. • Benchmarked AI model responses on safety and consistency. • Addressed logical reasoning gaps through targeted feedback. • Enhanced response reliability via systematic criteria development.

2024 - Present

AI Content & Prompt Optimization Specialist

TextPrompt Response Writing SFT
As an AI Content & Prompt Optimization Specialist, I designed advanced prompts to simulate diverse edge cases and challenge language model robustness. I constructed structured training datasets exceeding 30,000 words with strict logical coherence and applied critical review to enhance content reasoning and clarity. This role required applying expert prompt engineering skills for high-performance LLM fine-tuning. • Developed complex prompts to test LLM performance limits. • Created large, logically consistent datasets for training use. • Reviewed and edited AI-generated text for clarity and tone. • Applied advanced prompt engineering for edge case scenarios.

As an AI Content & Prompt Optimization Specialist, I designed advanced prompts to simulate diverse edge cases and challenge language model robustness. I constructed structured training datasets exceeding 30,000 words with strict logical coherence and applied critical review to enhance content reasoning and clarity. This role required applying expert prompt engineering skills for high-performance LLM fine-tuning. • Developed complex prompts to test LLM performance limits. • Created large, logically consistent datasets for training use. • Reviewed and edited AI-generated text for clarity and tone. • Applied advanced prompt engineering for edge case scenarios.

2024 - Present

AI Training & Data Annotation Specialist

TextRLHF
As an AI Training & Data Annotation Specialist, I optimized supervised machine learning models through expert annotation and labeling of complex text datasets. My work included ranking AI model outputs using RLHF to enhance reasoning and truthfulness, alongside thorough evaluation against defined safety and accuracy metrics. I maintained consistency and quality through rigorous data analysis and correction of dataset inconsistencies. • Annotated text data sets with high precision methodologies. • Performed RLHF-based output ranking for LLM reasoning improvements. • Evaluated AI responses for accuracy, safety, and proper tone. • Conducted logical analysis to eliminate inconsistencies in data.

As an AI Training & Data Annotation Specialist, I optimized supervised machine learning models through expert annotation and labeling of complex text datasets. My work included ranking AI model outputs using RLHF to enhance reasoning and truthfulness, alongside thorough evaluation against defined safety and accuracy metrics. I maintained consistency and quality through rigorous data analysis and correction of dataset inconsistencies. • Annotated text data sets with high precision methodologies. • Performed RLHF-based output ranking for LLM reasoning improvements. • Evaluated AI responses for accuracy, safety, and proper tone. • Conducted logical analysis to eliminate inconsistencies in data.

2024 - Present

Education

U

University of Calabar

Doctor of Pharmacy, Pharmacy

Doctor of Pharmacy
2024

Work History

Y

YouTube

Content Strategist

N/A
2024 - Present