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Harrison A.

Harrison A.

Freelance AI Trainer & Data Annotator (Remote)

Kenya flagNairobi, Kenya

Key Skills

Software

LabelboxLabelbox
CloudFactoryCloudFactory
AppenAppen
ClickworkerClickworker
OneFormaOneForma
V7 LabsV7 Labs
TolokaToloka
TelusTelus
CVATCVAT

Top Subject Matter

Computer vision for AI training
NLP (sentiment, intent, categorization)
Audio data for AI training

Top Data Types

ImageImage
TextText
AudioAudio

Top Task Types

TranscriptionTranscription
Bounding BoxBounding Box
PolygonPolygon
ClassificationClassification
SegmentationSegmentation
Point/Key PointPoint/Key Point
Text GenerationText Generation
CuboidCuboid
Data CollectionData Collection
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
Object DetectionObject Detection
Entity (NER) ClassificationEntity (NER) Classification

Freelancer Overview

Freelance AI Trainer & Data Annotator (Remote). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT and Microsoft Excel. Education includes Bachelor of Science, Maseno University (2026). AI-training focus includes data types such as Image and Text and labeling workflows including Object Detection, Segmentation, and Entity (NER) Classification.

Labeling Experience

Data Entry Assistant

TextTextData CollectionData Collection

Provided data labeling-adjacent support by entering and verifying large volumes of data for organizational recordkeeping. Maintained data accuracy during verification and supported administrative and reporting workflows. Used spreadsheets to manage and update records while following accuracy-focused processes.• Entered and verified large volumes of data with high accuracy. • Organized digital records and maintained confidential information. • Supported reporting tasks using Excel and Google Sheets. • Improved workflow efficiency through accurate data management practices.

2025 - 2026

Semantic and Segmentation

ImageImageBounding BoxBounding Box

In semantic segmentation and instance segmentation within a dataset annotation task, there are processes through which images will be labeled based on the outlines of objects or parts of an image according to certain project requirements. In semantic segmentation, the pixels are assigned classes that may include, but are not limited to, crops, soil, or roads, whereby no individual object is separated from others. In instance segmentation, each object in the same class has to be segmented and labeled individually; for example, different crop plants within a single farm.

2025 - 2026

Agricultural Dataset Annotation and Analysis

OtherImageImageBounding BoxBounding Box

Annotation and analysis of agricultural images and LiDAR data through detection of crop types, livestock, pests, soil status, machinery, and terrain for use in AI and computer vision algorithms employed in intelligent agriculture applications, including smart farming and precision agriculture.

2023 - 2025
CVAT

Freelance AI Trainer & Data Annotator (Remote)

CVATCVATImageImageObject DetectionObject DetectionSegmentationSegmentation

Freelance AI Trainer and data annotator producing labeled computer vision datasets for machine learning workflows. Responsibilities included bounding box annotation, semantic segmentation, and object detection labeling while verifying label accuracy against project guidelines. Work included iterative review/correction cycles to ensure consistent annotations across large batches. • Annotated images and videos • Applied bounding boxes and segmentation labels • Performed quality checks to maintain >95% accuracy • Followed and updated workflows based on client instructions

2023 - 2025

CVAT for bounding boxes and LiDAR point cloud labeling(Remote)

ImageImageBounding BoxBounding Box

This particular project was aimed at the training of AI algorithms for smart farming based on image and LiDAR datasets. Within the process of annotation, there have been established different kinds of agricultural objects such as crops, livestock, agricultural machinery, pests, etc., by means of bounding boxes with the help of CVAT tool, and LiDAR points cloud labels, which helped to classify terrain, vegetation, and spatial objects for further 3D mapping and analytics. In the framework of this project, large volumes of data had to be analyzed and processed that meant thousands of images and point cloud frames. High-quality annotations have been performed according to all the standards and criteria.

2022 - 2024

Education

M

Maseno University

Bachelor of Science, Business Administration

Bachelor of Science
2026 - 2026
M

Mawego Technical College

Certificate, Computer Applications

Certificate
Not specified

Work History

K

Kengen Company Plc

Data Entry Assistant

Nairobi
2025 - 2026
A

Avala.ai

Data annotation

Kisumu
2024 - 2025