Viola M.

Key Skills

Software

CloudFactory

Sama

Top Subject Matter

Agriculture (Weed/Crop Classification)

General (Object Detection, Segmentation)

Top Data Types

Image

Video

Audio

Top Task Types

Classification

Segmentation

Polygon

Bounding Box

Point/Key Point

Object Detection

Transcription

Data Collection

Prompt + Response Writing (SFT)

Cuboid

Polyline

Entity (NER) Classification

Question Answering

Evaluation/Rating

Function Calling

Freelancer Overview

Data Annotation. Core strengths include CloudFactory and Sama. Education includes Bachelor of Science, Laikipia University (2018) and Certified Public Accountant, KASNEB (2022). AI-training focus includes data types such as Image and labeling workflows including Classification and Segmentation.

Labeling Experience

AI Data Trainer / Annotator

SamaImageSegmentation

I labeled large-scale image, video, and LiDAR datasets for object detection, segmentation, and classification, achieving high annotation accuracy for machine learning models. I maintained label consistency and quality standards, identifying edge cases to strengthen dataset integrity. I collaborated on refining annotation guidelines and conducted quality assurance across label sets. • Performed object detection, segmentation, and classification tasks. • Used standardized guidelines to annotate over 50,000 data points. • Applied structured reasoning to highlight anomalies and difficult samples. • Participated in guideline improvement and in-team quality control initiatives.

2023 - 2026

Data Annotation

CloudFactoryImageClassification

I annotated agricultural image datasets to identify and classify weed and crop species for machine learning training. I ensured label accuracy and consistency across varying environmental conditions in field-collected crop images. I followed strict protocols and collaborated to resolve ambiguous cases, enhancing dataset reliability for agricultural AI applications. • Distinguished between crop and weed based on visual characteristics. • Applied label guidelines for precise classification. • Used team reviews to refine consistency in annotation. • Contributed to high-quality datasets that supported crop monitoring AI models.

2020 - 2022

Education

Work History