Mark M.

Key Skills

Software

CVAT

LabelImg

Label Studio

Roboflow

Other

Top Subject Matter

Medical imaging

engineering diagrams/CAD

finance charts & documents

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Classification

Freelancer Overview

Freelance AI Data Annotator and Visual Data Reviewer. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include CVAT, LabelImg, and Label Studio. Education includes Bachelor of Engineering, Technical University of Kenya (2025) and Professional Development Course, University of Nairobi (2024). AI-training focus includes data types such as Image, Medical, and DICOM and labeling workflows including Bounding Box, Classification, and Evaluation.

Labeling Experience

Freelance AI Data Annotator and Visual Data Reviewer

CVATImageBounding Box

Provided image annotation and visual data review for AI model training across medical, engineering, and finance domains. Labeled objects using bounding boxes, polygons, classification tags, and segmentation-style labels while writing structured image descriptions for dataset consistency. Performed quality checks and compared AI-generated responses against image evidence to flag reasoning errors and missing details. • Annotated MRI/CT-related visuals by identifying anatomical regions, image quality issues, and visual patterns • Reviewed engineering visuals including CAD drawings, circuit schematics, and PCB layouts for correct component and layout interpretation • Annotated finance charts and documents, labeling charts, tables, dashboard screenshots, and related visual elements • Conducted dataset validation for accuracy, consistency, completeness, and adherence to project instructions

2024 - Present

Image Annotation and Dataset Quality Assistant (Independent Academic and AI Training Projects)

OtherImageClassification

Created and reviewed structured labels for normal image datasets intended for machine learning training. Identified image regions, objects, visual defects, measurement cues, labels, symbols, and chart-based information to support downstream computer vision tasks. Reviewed datasets for missing labels, inconsistent classes, unclear bounding areas, and duplicated or low-quality images, and documented labeling rationales. • Performed visual QA for healthcare, engineering design, financial documents, and technical diagram datasets • Detected and labeled objects/regions, including defects, cues, symbols, and chart elements • Checked labeling integrity for duplicates, omissions, class inconsistency, and low-quality images • Produced clear written justifications for why a label or interpretation was correct or incorrect

2023 - Present

Biomedical Engineering and Data Analysis Project Contributor

Contributed to biomedical engineering data analysis tasks involving medical imaging examples and clinical datasets. Used Python and MATLAB to clean datasets, compute descriptive statistics, validate device performance, and visualize trends. Applied medical imaging concepts such as MRI/CT preprocessing, anatomical structure recognition, and image enhancement basics to support analysis readiness. • Conducted applied statistical analysis to identify patterns in clinical and engineering datasets • Performed MRI/CT preprocessing and supported anatomical structure identification and image enhancement • Validated device performance using computed metrics and trend visualization across test conditions • Explored computational fluid dynamics concepts related to blood flow behavior and biomedical device performance

2022 - 2025

Education

Work History