Ayibiowu H.

Key Skills

Software

Other

Dataloop

CVAT

Encord

Labelbox

Label Studio

Roboflow

Tagtog

SuperAnnotate

Top Subject Matter

AI and Machine Learning Training Data — RLHF response evaluation, instruction-following quality assessment, model output ranking, conversational AI dataset creation, and prompt quality review. Backed by 7+ years building and evaluating live AI automation systems across 250+ real-world deployments.

Financial Services and Fintech — transaction classification, invoice and payment document annotation, fraud signal labelling, bank reconciliation data review, and compliance document tagging. Applied domain expertise from delivering AI-powered financial automation systems for fintech clients across Africa and North America.

Healthcare and Business Operations — clinical document classification, patient record annotation, GDPR-compliant data labelling, CRM and sales pipeline data tagging, and enterprise workflow annotation. Grounded in hands-on delivery of healthcare management platforms and operational automation systems for 100+ organisations.

Top Data Types

Document

Image

Video

Top Task Types

Function Calling

Data Collection

Fine-tuning

Transcription

Red Teaming

Classification

Segmentation

Computer Programming/Coding

RLHF

Freelancer Overview

AI Output Evaluator and Training Data Specialist. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Science, Adekunle Ajasin University (2022). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Entity (NER).

Labeling Experience

Annotation Quality Assurance Lead

OtherDocument

Led independent and freelance text/NLP annotation and AI evaluation for business operations, fintech, and healthcare training pipelines. Produced multi-class sentiment and intent labels, performed instruction-following quality assessments, and ranked/rated model outputs to support alignment. Created conversational AI training data including multi-turn dialogues, intents, and entities for chatbot systems. • Annotated text for sentence classification, NER, coreference resolution, and relation extraction across operational documents. • Labeled customer communications and support tickets using fine-grained sentiment and intent taxonomies. • Evaluated AI responses for accuracy, helpfulness, safety, and guideline adherence, including output ranking. • Labeled business/financial documents (invoices, contracts, statements) for information extraction and document AI models.

2022 - Present

AI Output Evaluator and Training Data Specialist

Text

Evaluated AI-generated outputs and supported RLHF-style preference and alignment assessment across 250+ real-world automation deployments. Reviewed model responses, classified edge cases, and flagged errors to ensure correct behavior for each domain and business logic. Applied structured quality frameworks to measure consistency and drive error rates below 2% in multi-step AI validation workflows. • Conducted response ranking and helpfulness/safety scoring as part of instruction-following evaluation. • Built and refined prompt libraries and instruction-following test cases to validate complex multi-condition scenarios. • Developed annotation schemas and labeling guidelines for financial document processing workflows. • Performed quality-checking and verification for healthcare record inputs/outputs, including GDPR compliance flag handling.

2019 - Present

Instructional Content Reviewer and QA Specialist

OtherDocumentData Collection

Reviewed, structured, and quality-assured large volumes of instructional content across multiple HR, CRM, project management, and occupational safety topics. Developed content classification systems and assessment frameworks to ensure accuracy, clarity, and completeness at scale. Calibrated and trained teams to use consistent rubrics, analogous to maintaining inter-annotator agreement in annotation work. • Applied structured rubrics to review accuracy, clarity, and completeness of training content. • Developed taxonomy/classification structures for consistent categorization across subjects and proficiency levels. • Trained instructors on standardized delivery to support consistent evaluation across teams. • Drafted assessment frameworks measuring learner understanding with consistent precision standards.

2018 - 2024

Education

Work History