Oluwatobiloba Musayayi

Key Skills

Software

OneForma

Appen

Other

Top Subject Matter

Large Language Models (LLMs) and NLP

Top Data Types

Text

Image

Video

Top Task Types

Bounding Box

Object Detection

Text Generation

RLHF

Transcription

Data Collection

Evaluation/Rating

Prompt + Response Writing (SFT)

Freelancer Overview

AI Data Contributor. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OneForma, Appen, and Other. Education includes Master of Science, Tai Solarin University of Education (2026) and Bachelor of Science, Tai Solarin University of Education (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Data Contributor

OneformaText

As an AI Data Contributor at OneForma (Centific), I evaluated and ranked AI-generated responses using detailed rubrics for accuracy, tone, safety, and instruction adherence. I created challenging prompts to probe model behavior and identified hallucinations and weak reasoning chains. My work also included producing structured reference responses and reviewing peer contributions to maintain dataset quality. • Evaluated daily outputs and provided detailed feedback for model improvement. • Wrote adversarial prompts covering factual, creative, and multi-step reasoning tasks. • Identified and documented model hallucinations and edge-case failures. • Regularly met quality and output volume targets in a remote setting.

As an AI Data Contributor at OneForma (Centific), I evaluated and ranked AI-generated responses using detailed rubrics for accuracy, tone, safety, and instruction adherence. I created challenging prompts to probe model behavior and identified hallucinations and weak reasoning chains. My work also included producing structured reference responses and reviewing peer contributions to maintain dataset quality. • Evaluated daily outputs and provided detailed feedback for model improvement. • Wrote adversarial prompts covering factual, creative, and multi-step reasoning tasks. • Identified and documented model hallucinations and edge-case failures. • Regularly met quality and output volume targets in a remote setting.

2022 - Present

AI Evaluation Contributor (Freelance)

OtherText

As an independent AI Evaluation Contributor, I evaluated AI outputs for tone, safety, factual correctness, and misuse potential across various sensitive topics. I used adversarial techniques to expose weaknesses and conducted research to validate model claims. I provided structured written feedback aligned to unique client guidelines and evolving benchmarks. • Uncovered model vulnerabilities through adversarial testing and analysis. • Supplemented evaluations with source-backed, fact-checked reasoning. • Managed multiple client projects with consistent, deadline-driven delivery. • Produced comprehensive evaluations supporting ongoing LLM safety and performance improvement.

As an independent AI Evaluation Contributor, I evaluated AI outputs for tone, safety, factual correctness, and misuse potential across various sensitive topics. I used adversarial techniques to expose weaknesses and conducted research to validate model claims. I provided structured written feedback aligned to unique client guidelines and evolving benchmarks. • Uncovered model vulnerabilities through adversarial testing and analysis. • Supplemented evaluations with source-backed, fact-checked reasoning. • Managed multiple client projects with consistent, deadline-driven delivery. • Produced comprehensive evaluations supporting ongoing LLM safety and performance improvement.

2023 - 2024

AI Data Rater / Evaluator

AppenText

As an AI Data Rater and Evaluator at Appen, I assessed AI-generated content according to annotation guidelines focused on relevance, factual accuracy, and user intent. I performed side-by-side response comparisons and applied preference ranking for RLHF training. I maintained strong inter-annotator agreement and high evaluation volume with minimal rework. • Compared outputs to support training workflows for reinforcement learning from human feedback. • Evaluated various types of responses following strict criteria. • Ensured high annotation quality and consistency in a remote environment. • Delivered extensive evaluations to train and benchmark LLMs.

As an AI Data Rater and Evaluator at Appen, I assessed AI-generated content according to annotation guidelines focused on relevance, factual accuracy, and user intent. I performed side-by-side response comparisons and applied preference ranking for RLHF training. I maintained strong inter-annotator agreement and high evaluation volume with minimal rework. • Compared outputs to support training workflows for reinforcement learning from human feedback. • Evaluated various types of responses following strict criteria. • Ensured high annotation quality and consistency in a remote environment. • Delivered extensive evaluations to train and benchmark LLMs.

2021 - 2022

Education

Work History