For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
Jessee Wachira

Jessee Wachira

Assistant Architect in Contract Review, Compliance, and Legal Research

KENYA flag
Nairobi, Kenya
$15.00/hrExpertAppenClickworkerData Annotation Tech

Key Skills

Software

AppenAppen
ClickworkerClickworker
Data Annotation TechData Annotation Tech
MercorMercor
MindriftMindrift
RemotasksRemotasks

Top Subject Matter

Legal Services & Contract Review
Regulatory Compliance & Risk Analysis
Legal Research & Document Analysis

Top Data Types

TextText
DocumentDocument
VideoVideo

Top Task Types

Bounding Box
Segmentation
Classification
Object Detection
Text Generation
Text Summarization
Transcription
Data Collection

Freelancer Overview

Assistant Architect in Contract Review, Compliance, and Legal Research. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Education includes Bachelor of Architecture, Technical University of Kenya (2025) and Bachelor of Architectural Studies, Technical University of Kenya (2022).

ExpertEnglish

Labeling Experience

Geospatial Tiled Imagery

Geospatial Tiled ImageryBounding Box
Contributed to geospatial data annotation projects involving tiled satellite and aerial imagery on the Handshake platform. Responsibilities included identifying and labeling geographic features such as buildings, roads, vegetation, and land-use patterns using bounding box techniques in accordance with detailed annotation guidelines. Worked with high-resolution, large-scale spatial datasets requiring strong visual interpretation skills, spatial awareness, and consistency across tiled image segments. Ensured data quality through careful review, accurate object identification, and adherence to strict annotation standards. Handled large volumes of geospatial data efficiently while maintaining accuracy and consistency. This work supported the development of machine learning models for applications such as mapping, urban planning, environmental monitoring, and geospatial analysis.

Contributed to geospatial data annotation projects involving tiled satellite and aerial imagery on the Handshake platform. Responsibilities included identifying and labeling geographic features such as buildings, roads, vegetation, and land-use patterns using bounding box techniques in accordance with detailed annotation guidelines. Worked with high-resolution, large-scale spatial datasets requiring strong visual interpretation skills, spatial awareness, and consistency across tiled image segments. Ensured data quality through careful review, accurate object identification, and adherence to strict annotation standards. Handled large volumes of geospatial data efficiently while maintaining accuracy and consistency. This work supported the development of machine learning models for applications such as mapping, urban planning, environmental monitoring, and geospatial analysis.

2025 - 2026

Data Annotation

ImageObject Detection
Contributed to an AI data labeling project focused on image-based object detection within the Handshake platform. The work involved annotating images by accurately identifying and labeling objects using bounding boxes, ensuring consistency with predefined annotation guidelines. Tasks included reviewing image datasets, classifying visual elements, and validating annotations to maintain high data quality standards. Worked with large volumes of image data, requiring attention to detail, pattern recognition, and adherence to strict quality control processes. Regularly conducted self-review and participated in feedback loops to improve annotation accuracy and consistency.

Contributed to an AI data labeling project focused on image-based object detection within the Handshake platform. The work involved annotating images by accurately identifying and labeling objects using bounding boxes, ensuring consistency with predefined annotation guidelines. Tasks included reviewing image datasets, classifying visual elements, and validating annotations to maintain high data quality standards. Worked with large volumes of image data, requiring attention to detail, pattern recognition, and adherence to strict quality control processes. Regularly conducted self-review and participated in feedback loops to improve annotation accuracy and consistency.

2025 - 2026

Data Annotation

TextText Summarization
Worked on AI training and data annotation projects with Outlier, supporting the development of machine learning models through high-quality data labeling and evaluation. Responsibilities included reviewing and annotating text and image datasets, applying structured guidelines to ensure accuracy, consistency, and relevance of labeled data. Performed tasks such as content classification, quality evaluation, and data validation, ensuring outputs met strict quality benchmarks. Contributed to refining model performance by identifying inconsistencies, correcting errors, and providing feedback on annotation guidelines.

Worked on AI training and data annotation projects with Outlier, supporting the development of machine learning models through high-quality data labeling and evaluation. Responsibilities included reviewing and annotating text and image datasets, applying structured guidelines to ensure accuracy, consistency, and relevance of labeled data. Performed tasks such as content classification, quality evaluation, and data validation, ensuring outputs met strict quality benchmarks. Contributed to refining model performance by identifying inconsistencies, correcting errors, and providing feedback on annotation guidelines.

2025 - 2025

3D Sensor Classification

3D SensorClassification
Participated in a 3D sensor data classification project with CrowdGen Appen, focusing on labeling and categorizing spatial data generated from LiDAR and similar sensor technologies. Responsibilities included analyzing 3D point cloud data and accurately classifying objects such as vehicles, pedestrians, buildings, and environmental features according to predefined annotation guidelines. Ensured high-quality data output by applying consistent classification standards, conducting thorough reviews, and correcting misclassified elements to maintain dataset integrity. Worked with complex spatial datasets requiring strong attention to detail, spatial awareness, and pattern recognition.

Participated in a 3D sensor data classification project with CrowdGen Appen, focusing on labeling and categorizing spatial data generated from LiDAR and similar sensor technologies. Responsibilities included analyzing 3D point cloud data and accurately classifying objects such as vehicles, pedestrians, buildings, and environmental features according to predefined annotation guidelines. Ensured high-quality data output by applying consistent classification standards, conducting thorough reviews, and correcting misclassified elements to maintain dataset integrity. Worked with complex spatial datasets requiring strong attention to detail, spatial awareness, and pattern recognition.

2022 - 2025

Object Detection

ImageObject Detection
Worked on image-based object detection projects with Remotasks, focusing on annotating visual data using bounding boxes and segmentation techniques. Responsibilities included identifying and labeling objects such as vehicles, pedestrians, road features, and environmental elements according to detailed annotation guidelines. Ensured high-quality outputs by maintaining consistency, accuracy, and adherence to project standards across large image datasets. Performed quality checks and corrections to improve annotation reliability and meet client expectations. The role required strong attention to detail, visual analysis skills, and the ability to interpret complex instructions. Contributed to the development of computer vision models used in applications such as autonomous driving, mapping, and real-world environment recognition.

Worked on image-based object detection projects with Remotasks, focusing on annotating visual data using bounding boxes and segmentation techniques. Responsibilities included identifying and labeling objects such as vehicles, pedestrians, road features, and environmental elements according to detailed annotation guidelines. Ensured high-quality outputs by maintaining consistency, accuracy, and adherence to project standards across large image datasets. Performed quality checks and corrections to improve annotation reliability and meet client expectations. The role required strong attention to detail, visual analysis skills, and the ability to interpret complex instructions. Contributed to the development of computer vision models used in applications such as autonomous driving, mapping, and real-world environment recognition.

2021 - 2023

Education

T

Technical University of Kenya

Bachelor of Architecture, Architecture

Bachelor of Architecture
2023 - 2025
T

Technical University of Kenya

Bachelor of Architectural Studies, Architectural Studies

Bachelor of Architectural Studies
2019 - 2022

Work History

S

Sayoric International LTD

Graduate Architect

Nairobi
2025 - Present
D

Design Barn

Architectural Technician

Nairobi
2024 - 2024