Agustine Nyaanga

Key Skills

Software

Other

Micro1

CloudFactory

Sama

V7 Labs

Internal/Proprietary Tooling

Toloka

Mindrift

iMerit

Top Subject Matter

Computer Vision (Animal and Human Motion)

Computer Vision (Scene/Cinematic Understanding)

Geospatial/3D Mapping/Structural Analysis

Top Data Types

Video

Image

3D Sensor

Top Task Types

Point/Key Point

Action Recognition

Segmentation

Bounding Box

Cuboid

Polyline

Data Collection

Freelancer Overview

Data Annotation Expert. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Micro1, and CloudFactory. Education includes Bachelor of Science, Kenya Methodist University (2025) and Kenya Certificate of Secondary Education, St. Joseph Seminary (2018). AI-training focus includes data types such as Video, Geospatial, and Tiled Imagery and labeling workflows including Point, Key Point, and Action Recognition.

Labeling Experience

Data Annotation Expert

OtherVideoPoint Key Point

As a Data Annotation Expert at Innodata, I annotated rodeo events by placing skeletal key points (SKPs) on bulls/horses and riders for detailed motion tracking. I drew 2D bounding boxes around animals and riders to facilitate object detection in dynamic video datasets. My work included performing video annotation focused on describing user actions, movements, and environmental details with high accuracy. • Placed skeletal key points for motion tracking in video. • Drew bounding boxes to enable object detection. • Maintained 98% annotation accuracy and consistency. • Generated high-quality data for various computer vision projects.

As a Data Annotation Expert at Innodata, I annotated rodeo events by placing skeletal key points (SKPs) on bulls/horses and riders for detailed motion tracking. I drew 2D bounding boxes around animals and riders to facilitate object detection in dynamic video datasets. My work included performing video annotation focused on describing user actions, movements, and environmental details with high accuracy. • Placed skeletal key points for motion tracking in video. • Drew bounding boxes to enable object detection. • Maintained 98% annotation accuracy and consistency. • Generated high-quality data for various computer vision projects.

2025 - Present

Video Annotation Expert

Micro1VideoAction Recognition

As a Video Annotation Expert at Micro1, I annotated over 50 video clips, providing scene progression, lighting, and character/camera movements with precise timestamps. My work required applying a filmmaker’s lens to describe lighting and camera operations effectively. I consistently maintained 95% or higher annotation accuracy, leveraging strict quality assurance protocols. • Labeled scene progression and action details in video data. • Described lighting and cinematic elements. • Applied precise timestamps for action recognition accuracy. • Collaborated with remote teams to improve workflow.

As a Video Annotation Expert at Micro1, I annotated over 50 video clips, providing scene progression, lighting, and character/camera movements with precise timestamps. My work required applying a filmmaker’s lens to describe lighting and camera operations effectively. I consistently maintained 95% or higher annotation accuracy, leveraging strict quality assurance protocols. • Labeled scene progression and action details in video data. • Described lighting and cinematic elements. • Applied precise timestamps for action recognition accuracy. • Collaborated with remote teams to improve workflow.

2025 - 2025

Data Labeller and Annotator

CloudfactorySegmentation

As a Data Labeller and Annotator at CloudFactory, I annotated roof geometry data to refine computer vision models for accurate 3D mapping and structural analysis. My responsibilities included processing large datasets for spatial recognition, maintaining a 98% annotation accuracy rate. I contributed to improving real-world model performance by generating precise ground truth data. • Labeled roof geometry for spatial modeling tasks. • Processed diverse geospatial datasets efficiently. • Contributed to structural feature segmentation. • Maintained high annotation quality standards.

As a Data Labeller and Annotator at CloudFactory, I annotated roof geometry data to refine computer vision models for accurate 3D mapping and structural analysis. My responsibilities included processing large datasets for spatial recognition, maintaining a 98% annotation accuracy rate. I contributed to improving real-world model performance by generating precise ground truth data. • Labeled roof geometry for spatial modeling tasks. • Processed diverse geospatial datasets efficiently. • Contributed to structural feature segmentation. • Maintained high annotation quality standards.

2024 - 2025

3D LiDAR Data Annotator

Sama3D SensorBounding Box

As a 3D LiDAR Data Annotator at Sama AI, I labeled point clouds for training autonomous vehicle perception systems. My work focused on precise object detection tasks for identifying pedestrians, vehicles, and other entities. I contributed to workflow refinements, which reduced annotation error rates by 15% and supported time-sensitive ML pipelines. • Labeled 3D point cloud data for object detection. • Focused on vehicular and pedestrian segmentation. • Implemented efficient workflows for tight deadlines. • Supported ML model validation through accurate labels.

As a 3D LiDAR Data Annotator at Sama AI, I labeled point clouds for training autonomous vehicle perception systems. My work focused on precise object detection tasks for identifying pedestrians, vehicles, and other entities. I contributed to workflow refinements, which reduced annotation error rates by 15% and supported time-sensitive ML pipelines. • Labeled 3D point cloud data for object detection. • Focused on vehicular and pedestrian segmentation. • Implemented efficient workflows for tight deadlines. • Supported ML model validation through accurate labels.

2023 - 2024

Education

Work History