Kingsley Isichei

Key Skills

Software

Remotasks

Telus

Labelbox

Appen

Top Subject Matter

Computer Vision

Model QA and Output Evaluation

Object Detection / Computer Vision

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Segmentation

Freelancer Overview

AI Data Annotator / Content Rater. Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Remotasks, Telus, and Labelbox. Education includes Bachelor of Science, Federal University of Agriculture, Makurdi. AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Evaluation, and Rating.

Labeling Experience

AI Data Annotator / Content Rater

RemotasksImageBounding Box

As an AI Data Annotator and Content Rater, I annotated over 50,000 images and video frames using advanced techniques such as bounding boxes, polygons, and classification. I maintained high annotation accuracy standards and executed daily labeling tasks with consistent speed and quality. My responsibilities included quality assurance, adherence to evolving guidelines, and dataset validation. • Consistently delivered 98–99% QA accuracy. • Rated and evaluated text and multimedia content for relevance and safety. • Reduced annotation inconsistencies by more than 15% through error detection. • Worked across multiple annotation frameworks and platforms, primarily Remotasks and Labelbox.

As an AI Data Annotator and Content Rater, I annotated over 50,000 images and video frames using advanced techniques such as bounding boxes, polygons, and classification. I maintained high annotation accuracy standards and executed daily labeling tasks with consistent speed and quality. My responsibilities included quality assurance, adherence to evolving guidelines, and dataset validation. • Consistently delivered 98–99% QA accuracy. • Rated and evaluated text and multimedia content for relevance and safety. • Reduced annotation inconsistencies by more than 15% through error detection. • Worked across multiple annotation frameworks and platforms, primarily Remotasks and Labelbox.

2023 - Present

AI Quality Analyst (Contract)

TelusText

In the role of AI Quality Analyst, I evaluated AI-generated outputs for both text and visual data, ensuring alignment with expected objectives. I conducted root-cause error analysis to improve dataset quality and collaborated with annotation teams to refine labeling guidelines. Structured QA processes were implemented to boost reliability and flag ambiguous or edge-case data. • Improved dataset quality scores by over 20%. • Worked in close coordination with annotation and QA teams. • Flagged ambiguous data points to enhance model training. • Employed structured QA frameworks in remote settings with Telus.

In the role of AI Quality Analyst, I evaluated AI-generated outputs for both text and visual data, ensuring alignment with expected objectives. I conducted root-cause error analysis to improve dataset quality and collaborated with annotation teams to refine labeling guidelines. Structured QA processes were implemented to boost reliability and flag ambiguous or edge-case data. • Improved dataset quality scores by over 20%. • Worked in close coordination with annotation and QA teams. • Flagged ambiguous data points to enhance model training. • Employed structured QA frameworks in remote settings with Telus.

2022 - 2022

Content Moderation & Rating Project

AppenText

In a Content Moderation & Rating Project, I evaluated online text content for policy compliance, search relevance, and user safety. Structured rating systems were applied to classify, moderate, and refine dataset utility. My role also included identifying harmful or misleading content to improve user experience. • Assessed and rated various forms of online text content. • Enhanced search relevance based on structured metrics. • Applied platform policy guidelines consistently. • Contributed to safer online platforms through diligent moderation.

In a Content Moderation & Rating Project, I evaluated online text content for policy compliance, search relevance, and user safety. Structured rating systems were applied to classify, moderate, and refine dataset utility. My role also included identifying harmful or misleading content to improve user experience. • Assessed and rated various forms of online text content. • Enhanced search relevance based on structured metrics. • Applied platform policy guidelines consistently. • Contributed to safer online platforms through diligent moderation.

Not specified

Computer Vision Annotation Project

LabelboxImageSegmentation

For a Computer Vision Annotation Project, I labeled datasets using bounding boxes and segmentation masks to facilitate object detection modeling. Labeling adhered strictly to taxonomy standards, ensuring the accuracy and utility of annotated data. These efforts contributed to improved dataset robustness for machine learning applications. • Worked with segmentation masks for robust object detection. • Ensured labeling consistency and taxonomy adherence. • Enhanced quality of annotated data for computer vision tasks. • Utilized tools such as Labelbox and Supervisely for detailed annotations.

For a Computer Vision Annotation Project, I labeled datasets using bounding boxes and segmentation masks to facilitate object detection modeling. Labeling adhered strictly to taxonomy standards, ensuring the accuracy and utility of annotated data. These efforts contributed to improved dataset robustness for machine learning applications. • Worked with segmentation masks for robust object detection. • Ensured labeling consistency and taxonomy adherence. • Enhanced quality of annotated data for computer vision tasks. • Utilized tools such as Labelbox and Supervisely for detailed annotations.

Not specified

Education

Work History