Adesanmi Adekuoroye

Key Skills

Software

CVAT

Other

Lionbridge

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Emotion Recognition

Entity Ner Classification

Evaluation Rating

Object Detection

Polygon

Prompt Response Writing SFT

RLHF

Segmentation

Text Generation

Transcription

Translation Localization

Freelancer Overview

I am a detail-oriented Data Annotation Specialist and QA Expert with over four years of experience supporting AI model training, search relevance evaluation, and content quality review. My work spans platforms like Mindrift and Upwork, where I have evaluated search engine results, reviewed e-commerce product listings, and compared AI-generated responses for accuracy, safety, and helpfulness. I excel at providing constructive feedback to improve data quality and consistently meet accuracy targets in high-volume annotation tasks. With a strong background in Biology and academic research, I bring analytical rigor and a commitment to excellence in every project, whether in NLP, e-commerce, or content moderation. My skills include quality assurance, search relevance rating, AI response evaluation, and performance review, making me well-equipped to support high-quality AI training data initiatives.

Labeling Experience

LLM Response Evaluation & RLHF Ranking Project

LionbridgeTextRLHFEvaluation Rating

Participated in Large Language Model (LLM) training through response evaluation, ranking, and supervised fine-tuning (SFT) tasks. Assessed outputs for accuracy, relevance, safety, and instruction adherence. Provided structured feedback to improve model alignment and overall response quality within RLHF workflows.

Participated in Large Language Model (LLM) training through response evaluation, ranking, and supervised fine-tuning (SFT) tasks. Assessed outputs for accuracy, relevance, safety, and instruction adherence. Provided structured feedback to improve model alignment and overall response quality within RLHF workflows.

2025 - 2025

Autonomous Driving Object Detection & Semantic Segmentation Project

CVATImageBounding BoxSegmentation

Annotated large-scale image datasets for autonomous driving models using CVAT. Responsibilities included precise bounding box and polygon segmentation for vehicles, pedestrians, traffic signs, and road infrastructure. Ensured high annotation accuracy through strict quality control processes and adherence to detailed labeling guidelines. Collaborated with QA teams to maintain consistency across thousands of frames and improve model training performance.

Annotated large-scale image datasets for autonomous driving models using CVAT. Responsibilities included precise bounding box and polygon segmentation for vehicles, pedestrians, traffic signs, and road infrastructure. Ensured high annotation accuracy through strict quality control processes and adherence to detailed labeling guidelines. Collaborated with QA teams to maintain consistency across thousands of frames and improve model training performance.

2025 - 2025

Named Entity Recognition (NER) for Financial Documents

OtherTextEntity Ner ClassificationClassification

Performed Named Entity Recognition (NER) and text classification on financial documents, annotating entities such as organizations, monetary values, dates, and financial instruments. Followed detailed guidelines to ensure high accuracy and consistency, contributing to improved NLP model performance and reliable information extraction.

Performed Named Entity Recognition (NER) and text classification on financial documents, annotating entities such as organizations, monetary values, dates, and financial instruments. Followed detailed guidelines to ensure high accuracy and consistency, contributing to improved NLP model performance and reliable information extraction.

2024 - 2025

Education

Work History