Joseph Ogoliebune

Key Skills

Software

Snorkel AI

Data Annotation Tech

Labelbox

Top Subject Matter

Computer Vision

Bias Detection in Recruitment AI

Top Data Types

Image

Text

Audio

Top Task Types

Classification

Object Detection

Question Answering

Text Summarization

Text Generation

Freelancer Overview

Data Annotation Specialist for Multimango Project. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox and Snorkel AI. Education includes Manyx Press (, Designer (2020). AI-training focus includes data types such as Image and Document and labeling workflows including Classification.

Labeling Experience

Data Annotation Specialist for Multimango Project

LabelboxImageClassification

I annotated image-text pairs for a custom computer vision project. This work involved using Python and OpenClip to classify and label images according to project specifications. I ensured high-quality image labeling to enable model training and accurate AI predictions. • Processed and annotated large-scale image datasets. • Used Python scripting for data preprocessing and annotation. • Followed strict labeling guidelines for project consistency. • Contributed to the development and evaluation of a computer vision model.

I annotated image-text pairs for a custom computer vision project. This work involved using Python and OpenClip to classify and label images according to project specifications. I ensured high-quality image labeling to enable model training and accurate AI predictions. • Processed and annotated large-scale image datasets. • Used Python scripting for data preprocessing and annotation. • Followed strict labeling guidelines for project consistency. • Contributed to the development and evaluation of a computer vision model.

2026 - Present

Data Annotation and Bias Auditor

Snorkel AIDocumentClassification

I built and audited a toolkit for demographic bias detection in training datasets. My work focused on annotating and evaluating data for fairness in automated recruitment AI. I identified and flagged biased instances in text and document data to improve data quality. • Audited datasets to assess demographic representation. • Annotated text and tabular data for bias and fairness issues. • Generated transparent data lineage reports. • Used Snorkel AI for annotation management and bias detection tasks.

I built and audited a toolkit for demographic bias detection in training datasets. My work focused on annotating and evaluating data for fairness in automated recruitment AI. I identified and flagged biased instances in text and document data to improve data quality. • Audited datasets to assess demographic representation. • Annotated text and tabular data for bias and fairness issues. • Generated transparent data lineage reports. • Used Snorkel AI for annotation management and bias detection tasks.

2023 - 2023

Education

Work History