Tobias M.

Key Skills

Software

Dataloop

CVAT

Labelbox

Roboflow

Sama

Top Subject Matter

Computer vision (image and lidar annotation) for ML model development

AI/ML training for image and lidar annotation

Legal Services & Contract Review

Top Data Types

Image

Text

Document

Top Task Types

Segmentation

Classification

Freelancer Overview

Image Annotation & Transcription (Digital DivideData). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include V7, Dataloop, and CVAT. Education includes Diploma in Health Records and Information Technology, Kabete National Polytechnic (2023) and High School Certificate (KCSE), Murang'a High School (2018). AI-training focus includes data types such as Image, Geospatial, and Tiled Imagery and labeling workflows including Segmentation and Classification.

Labeling Experience

Image Annotation & Transcription (Digital DivideData)

ImageSegmentation

Performed image annotation to support machine learning dataset creation. Ensured annotations were accurate, consistent, and complete to maintain dataset quality for downstream model training. Met labeling deadlines while applying strong attention to detail to reduce errors and improve usability of labeled outputs. • Annotated images using established labeling guidelines • Conducted quality checks to ensure label accuracy • Coordinated task completion to meet delivery timelines • Supported transcription work as part of data preparation workflows

2024 - Present

Training in Machine Learning and AI (Samasource)

SamaClassification

Completed a short AI and machine learning training focused on image and lidar annotation. Learned methodologies and best practices for preparing labeled data to improve model performance and efficiency. Built foundational understanding of how dataset labeling is applied within AI and machine learning projects. • Specialized in image and lidar annotation methodologies • Learned industry-standard labeling practices for ML pipelines • Practiced annotation approaches to enhance accuracy and efficiency • Gained understanding of dataset labeling impact on AI model outcomes

Not specified

Education

Work History