Oluwakolade A.

Key Skills

Software

Other

Mercor

Micro1

Top Subject Matter

AI Model Training - Multimodal Evaluation

Finance - Government Records Management and Financial Documentation

Engineering - Machinery and Power

Top Data Types

Image

Video

Text

Top Task Types

Classification

Data Collection

RLHF

Evaluation/Rating

Question Answering

Freelancer Overview

Clerical Officer, Nigerian Customs Service — Finance Department (document classification and structured record digitizat. Brings 4+ 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 Engineering, Federal University Oye-Ekiti (2024). AI-training focus includes data types such as Document and labeling workflows including Classification and Data Collection.

Labeling Experience

Clerical Officer, Nigerian Customs Service — Finance Department (document classification and structured record digitization)

DocumentClassification

Processed and classified high volumes of sensitive government correspondence for routing and recordkeeping purposes. Digitized financial and personnel documents into structured archives with strict accuracy and audit-readiness requirements. Maintained consistent data entry practices across registers and correspondence logs to reduce errors and improve reliability. • Classified and routed incoming documents from multiple sources. • Digitised records into structured, searchable archives. • Managed personnel file registry tracking across departmental stages. • Standardised data entry practices across logs and registers.

2025 - 2026

AI Model Trainer

ImageEvaluation/Rating

Evaluated AI generated images and videos on Outlier by comparing two model outputs per prompt. For each task, I reviewed both outputs across set criteria and selected the stronger one. For images, criteria included how well the output followed the prompt, visual quality, and the absence of AI artifacts. For example, given a prompt like "create an image of Yoma playing football," I judged which of the two generated images better represented the subject, the action, and overall realism. For videos, I assessed sound quality, visual consistency, and artifact-free output by flagging things like unnatural motion, audio sync issues, or visible generation errors. Results were submitted as structured evaluations.

2025 - 2025

AI Model Trainer and Prompter

Computer Code ProgrammingRLHF

Reviewed and compared AI-generated responses across coding and UI/UX design tasks. For each prompt, I picked the stronger of two model outputs, judging on code correctness, design quality, and how well it fit the brief. Tasks covered multiple categories, one example was evaluating whether a model could redesign a basic stopwatch into a wearable digital watch UI. Each task ran through five feature enhancements, and the best response was submitted as a JSON evaluation.

2024 - 2024

Agricultural Engineering Intern, Ondo State Ministry of Agriculture (field data collection and technical documentation)

OtherDocumentData Collection

Collected and recorded field/engineering data and produced technical reports aligned to departmental planning and regulatory standards. Analyzed collected data to identify system inefficiencies and proposed evidence-backed improvements. Documented project deliverables and specifications with careful measurement and data interpretation habits suitable for annotation and quality control. • Collected and recorded field data for agricultural processes. • Produced technical reports for departmental planning. • Analyzed data to identify inefficiencies and recommend improvements. • Documented deliverables/specifications to institutional standards.

2023 - 2024

Education

Work History