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Hi, I'm Sharon Ann, a highly skilled Data and Image Annotator with over six years of experience in preparing high-quality datasets for AI training in various industries. I've worked remotely with diverse teams, annotating images, videos, and LiDAR data to help power cutting-edge AI technologies, especially in autonomous driving, retail, surveillance, and sports. I'm passionate about delivering accurate and clean data and have expertise in multiple annotation techniques including semantic segmentation and 3D labeling. I'm dedicated to continuous learning and helping improve AI models by providing reliable data annotation services.…Hi, I'm Sharon Ann, a highly skilled Data and Image Annotator with over six years of experience in preparing high-quality datasets for AI training in various industries. I've worked remotely with diverse teams, annotating images, videos, and LiDAR data to help power cutting-edge AI technologies, especially in autonomous driving, retail, surveillance, and sports. I'm passionate about delivering accurate and clean data and have expertise in multiple annotation techniques including semantic segmentation and 3D labeling. I'm dedicated to continuous learning and helping improve AI models by providing reliable data annotation services.

Sharon Ann

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Hi, I'm Sharon Ann, a highly skilled Data and Image Annotator with over six years of experience in preparing high-quality datasets for AI training in various industries. I've worked remotely with diverse teams, annotating images, videos, and LiDAR data to help power cutting-edge AI technologies, especially in autonomous driving, retail, surveillance, and sports. I'm passionate about delivering accurate and clean data and have expertise in multiple annotation techniques including semantic segmentation and 3D labeling. I'm dedicated to continuous learning and helping improve AI models by providing reliable data annotation services.…Hi, I'm Sharon Ann, a highly skilled Data and Image Annotator with over six years of experience in preparing high-quality datasets for AI training in various industries. I've worked remotely with diverse teams, annotating images, videos, and LiDAR data to help power cutting-edge AI technologies, especially in autonomous driving, retail, surveillance, and sports. I'm passionate about delivering accurate and clean data and have expertise in multiple annotation techniques including semantic segmentation and 3D labeling. I'm dedicated to continuous learning and helping improve AI models by providing reliable data annotation services.

Available to hire

Hi, I’m Sharon Ann, a highly skilled Data and Image Annotator with over six years of experience in preparing high-quality datasets for AI training in various industries. I’ve worked remotely with diverse teams, annotating images, videos, and LiDAR data to help power cutting-edge AI technologies, especially in autonomous driving, retail, surveillance, and sports.

I’m passionate about delivering accurate and clean data and have expertise in multiple annotation techniques including semantic segmentation and 3D labeling. I’m dedicated to continuous learning and helping improve AI models by providing reliable data annotation services.

Skills

AI Data Labelling

CVAT

V7 Labs

Experience Level

AI Data Labelling

Expert

CVAT

Expert

V7 Labs

Expert

Language

English

Fluent

Swahili

Fluent

Work Experience

Computer Vision Annotator at Remotasks (Scale.ai)

December 31, 2024 - July 12, 2025

Annotated video and image datasets using bounding boxes, cuboids and polygons for self-driving cars. Worked on high-complexity road scenes involving traffic signs, lane markings and pedestrians. Participated in quality assurance reviews and trained new annotators.

Sports Data Annotator at Talent Match Kenya

December 31, 2023 - July 12, 2025

Labeled frames for sports videos with key-point and pose estimation to track player movements. Helped improve object tracking models by providing clean time stamped video annotations. Focused on sports like football and athletics including player identification and action recognition.

Image & Text Annotator at Spare5 (MightyAI)

December 31, 2021 - July 12, 2025

Annotated diverse image data for retail and mapping projects. Tagged and categorized product images for e-commerce training data. Contributed to early autonomous vehicle LiDAR projects through detailed labeling tasks.

Multi-domain Annotator at Appen (Figure Eight)

December 31, 2023 - July 12, 2025

Worked on multiple projects including sentiment analysis, image tagging and segmentation. Participated in a legal data annotation task involving document labeling and entity recognition. Performed quality assurance for peer-submitted tasks.

Polygon & Segmentation Specialist at Sequence.work

December 31, 2022 - July 12, 2025

Focused on instance segmentation for fashion and retail datasets. Used LabelBox and Makesense.ai to segment clothing, accessories and background environments.

Image & Video Annotator at Pactera

December 31, 2024 - July 12, 2025

Completed complex polygon annotations on surveillance footage for AI security training. Helped improve facial detection models by annotating various ethnicities and lighting conditions.

Audio & Text Contributor at Neevo

December 31, 2025 - July 12, 2025

Participated in image labeling and audio transcription tasks. Delivered consistent, high-quality data used in training voice and text recognition models.

Data Labeling Assistant at Execo

December 31, 2025 - July 12, 2025

Worked on body pose recognition and landmark annotation projects. Assisted in generating datasets for fitness AI and posture correction systems.

Annotation Team Member at CloudFactory

December 31, 2023 - July 12, 2025

Collaborated in a team to deliver large volumes of labeled data on tight deadlines. Contributed to projects involving image segmentation and medical image review.

Education

Bachelor of Computer Science at Kenyatta University

January 1, 2018 - December 31, 2022

Qualifications

Data Annotation

May 18, 2020 - July 13, 2025

Industry Experience

Transportation & Logistics, Retail, Professional Services, Media & Entertainment, Software & Internet, Agriculture & Mining

Player Movement and Event Annotation in Football Matches

Data AnnotatorSport Annotator This project involved detailed annotation of football match footage, focusing on player movements, ball possession, pass success/failure, defensive actions and event classification.…

Data Annotator

Image Segmentation CVAT

This project focused on annotating indoor objects to train AI models for scene segmentation tasks. Using CVAT, I manually labeled and masked elements such as plants, walls and floors with high precision, ensuring clear layer separation and accurate representation of each object. This meticulous annotation process enhances the performance of AI models in understanding and distinguishing indoor environments, benefiting applications in robotics navigation, interior mapping and augmented reality experiences.…This project focused on annotating indoor objects to train AI models for scene segmentation tasks. Using CVAT, I manually labeled and masked elements such as plants, walls and floors with high precision, ensuring clear layer separation and accurate representation of each object. This meticulous annotation process enhances the performance of AI models in understanding and distinguishing indoor environments, benefiting applications in robotics navigation, interior mapping and augmented reality experiences.

Data Annotator

SKU Annotation for Retail Items

Data Annotation This project aimed to support automated retail inventory systems by accurately labeling individual SKUs in store shelf images. To achieve this, hundreds of retail products were annotated using bounding boxes, allowing for clear distinction between product types and enabling SKU-level classification. The annotated data was used to train object recognition models capable of real-time stock monitoring. As a result, the project significantly improved inventory accuracy and reduced the need for manual audits, streamlining retail operations and enhancing shelf management efficiency.…Data Annotation This project aimed to support automated retail inventory systems by accurately labeling individual SKUs in store shelf images. To achieve this, hundreds of retail products were annotated using bounding boxes, allowing for clear distinction between product types and enabling SKU-level classification. The annotated data was used to train object recognition models capable of real-time stock monitoring. As a result, the project significantly improved inventory accuracy and reduced the need for manual audits, streamlining retail operations and enhancing shelf management efficiency.

Data Annotator

3D Annotation for Autonomous Freight Yard Navigation

I worked on the Autonomus 3D labeling project using Segment ai tool. Which aimed to enhance autonomous vehicle systems by accurately detecting and classifying 3D objects. I annotated Lidar data with tight 3D bounding boxes, applying size, orientation and activity rules to label trailers, vehicles, pedestrians, and more. My precise and consistent labeling improved model training data, supporting safer and more efficient navigation in yard and road environments.…I worked on the Autonomus 3D labeling project using Segment ai tool. Which aimed to enhance autonomous vehicle systems by accurately detecting and classifying 3D objects. I annotated Lidar data with tight 3D bounding boxes, applying size, orientation and activity rules to label trailers, vehicles, pedestrians, and more. My precise and consistent labeling improved model training data, supporting safer and more efficient navigation in yard and road environments.

Data Annotator

Person Detection Annotation in Public Scenes

This project focused on detailed annotation of individuals in crowded urban scenes using polygon segmentation. Each person was carefully outlined under the "person_poly" class to train advanced computer vision models for people counting, crowd density estimation, and smart surveillance. The annotations provide rich data for AI systems that require high-precision human detection in real-world, complex environments like marketplaces and public venues.…This project focused on detailed annotation of individuals in crowded urban scenes using polygon segmentation. Each person was carefully outlined under the "person_poly" class to train advanced computer vision models for people counting, crowd density estimation, and smart surveillance. The annotations provide rich data for AI systems that require high-precision human detection in real-world, complex environments like marketplaces and public venues.

Data Annotator

Pothole Detection Annotation

This project involved annotating images of roads to identify and label potholes using bounding boxes. The labeled dataset supports the development of AI models for automated road damage detection and maintenance planning. Each pothole was accurately marked under the class "pothole," enabling machine learning applications aimed at improving road safety and infrastructure monitoring.…

Data Annotator

Drone Detection Annotation

Data AnnotationBounding Box Data Labelling In this project, high-resolution images of drones were annotated using bounding boxes to train computer vision models for object detection. I labeled each drone in the image under the class "drone" using Supervisely. The work supports dataset preparation for AI applications such as drone identification, surveillance and autonomous navigation systems.…

Data Annotator

Keypoint Annotation Using Super Annotate

The goal was to annotate human figures in real-world images to build a high-quality dataset for training computer vision models in tasks like human detection and tracking.Using advanced annotation tools, data annotators precisely outlined individual humans, managed layers for clarity and ensured consistency across the dataset…

Data Annotator

Multi-Class Object Detection and Annotation for Food Items

Data AnnotationObject DetectionBounding Box The project aimed to annotate grocery items like apples, grapes and packaged goods for training a computer vision model in retail automation. Using Supervisely, I applied accurate bounding boxes and class labels across complex scenes with overlapping and occluded objects. My precise and consistent annotations improved data quality, supporting the development of a high-performing AI system for tasks such as inventory tracking, automated checkout and product recognition.…Data AnnotationObject DetectionBounding Box The project aimed to annotate grocery items like apples, grapes and packaged goods for training a computer vision model in retail automation. Using Supervisely, I applied accurate bounding boxes and class labels across complex scenes with overlapping and occluded objects. My precise and consistent annotations improved data quality, supporting the development of a high-performing AI system for tasks such as inventory tracking, automated checkout and product recognition.

Data Annotator

Bounding Box CVAT

Bounding Box Data Annotation Data Labelling I worked on annotating urban street scenes using CVAT to label multiple object classes including cars, bicycles, people and others with bounding boxes. This dataset was used to train a computer vision model for pedestrian and vehicle detection in city environments. My accurate labeling improved model precision and contributed to the development of safer autonomous navigation and traffic monitoring systems.…Bounding Box Data Annotation Data Labelling I worked on annotating urban street scenes using CVAT to label multiple object classes including cars, bicycles, people and others with bounding boxes. This dataset was used to train a computer vision model for pedestrian and vehicle detection in city environments. My accurate labeling improved model precision and contributed to the development of safer autonomous navigation and traffic monitoring systems.

Data Annotator

Aerial Land Segmentation Mapping

This project focused on the semantic segmentation of aerial drone imagery to classify agricultural and natural features such as fields, trees, ponds and roads. Using polygon annotation tools, each region was accurately labeled to support AI-driven land use monitoring, crop planning and environmental assessment. The task involved identifying boundaries and assigning predefined labels to optimize geospatial model training.I used LabelBox for this project.…This project focused on the semantic segmentation of aerial drone imagery to classify agricultural and natural features such as fields, trees, ponds and roads. Using polygon annotation tools, each region was accurately labeled to support AI-driven land use monitoring, crop planning and environmental assessment. The task involved identifying boundaries and assigning predefined labels to optimize geospatial model training.I used LabelBox for this project.

Data Annotator

Dental Image Segmentation

Data Annotation Image Segmentation This project involved precise polygon segmentation of individual teeth in high-resolution intraoral images to support AI models for dental diagnostics. Each tooth was annotated under the Tooth class, with additional classes reserved for identifying Caries, Cavity, and Crack in future phases. The labeled data aids in training machine learning models for automated detection of dental conditions, improving diagnostic accuracy and efficiency in digital dentistry tools.…Data Annotation Image Segmentation This project involved precise polygon segmentation of individual teeth in high-resolution intraoral images to support AI models for dental diagnostics. Each tooth was annotated under the Tooth class, with additional classes reserved for identifying Caries, Cavity, and Crack in future phases. The labeled data aids in training machine learning models for automated detection of dental conditions, improving diagnostic accuracy and efficiency in digital dentistry tools.

Data Annotator

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