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Gideon Kipkurui

Gideon Kipkurui

Data Annotator - AI Training

KENYA flag
Nairobi, Kenya
$7.00/hrIntermediateLabelbox

Key Skills

Software

LabelboxLabelbox

Top Subject Matter

No subject matter listed

Top Data Types

VideoVideo

Top Label Types

Polygon
Point Key Point
Segmentation

Freelancer Overview

I am a detail-oriented data annotator with hands-on experience labeling text, image, and audio data for AI training projects. My background in linguistics and fluency in both English and Swahili allow me to handle tasks like classification, sentiment analysis, and entity recognition with high accuracy. I am skilled in following complex guidelines, maintaining quality through personal checklists, and collaborating remotely using digital tools. My experience also includes transcription, translation, search engine evaluation, and supporting teams across time zones, making me adaptable and efficient in fast-paced, remote environments. I am committed to delivering consistent, high-quality data for NLP and computer vision applications.

IntermediateEnglish

Labeling Experience

Labelbox

atlas cupture

LabelboxVideoPolygonPoint Key Point
Atlas Capture is a platform used for large-scale image and video data annotation to support machine learning and computer vision projects across areas such as autonomous systems, surveillance, and AI research. Its scope includes data capture, human-in-the-loop labeling, and dataset preparation, with specific labeling tasks such as frame-by-frame video annotation, object tracking, bounding boxes, polygon-based segmentation, keypoint labeling, and classification of scenes or attributes. Projects handled through Atlas Capture are typically medium to large in size, ranging from hundreds of thousands to millions of images and thousands of video clips, often worked on by multiple annotators simultaneously. To ensure high-quality outputs, the platform follows strict quality measures including detailed annotation guidelines, multi-stage reviews, inter-annotator agreement checks, use of gold-standard reference data, random spot checks, and defined accuracy thresholds

Atlas Capture is a platform used for large-scale image and video data annotation to support machine learning and computer vision projects across areas such as autonomous systems, surveillance, and AI research. Its scope includes data capture, human-in-the-loop labeling, and dataset preparation, with specific labeling tasks such as frame-by-frame video annotation, object tracking, bounding boxes, polygon-based segmentation, keypoint labeling, and classification of scenes or attributes. Projects handled through Atlas Capture are typically medium to large in size, ranging from hundreds of thousands to millions of images and thousands of video clips, often worked on by multiple annotators simultaneously. To ensure high-quality outputs, the platform follows strict quality measures including detailed annotation guidelines, multi-stage reviews, inter-annotator agreement checks, use of gold-standard reference data, random spot checks, and defined accuracy thresholds

2025

Education

U

University of Nairobi

Bachelor of Arts, Linguistics

Bachelor of Arts
2023 - 2023

Work History

W

Woflow

Virtual Assistant

Nairobi
2023 - 2025