Key Skills

Software

CVAT

Top Subject Matter

Medical Imaging

General AI

Text and Mixed Data

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Segmentation

Freelancer Overview

AI Data Annotation & QA Specialist (Contract / Project-Based). Core strengths include CVAT. Education includes Professional Certificate, Columbia University (2023) and Bachelor of Science, University of Texas Health Science Center (2020). AI-training focus includes data types such as Image, Medical, and DICOM and labeling workflows including Bounding Box and Segmentation.

Labeling Experience

Medical Imaging AI Dataset Project Annotator

CVATSegmentation

As part of a Medical Imaging AI Dataset Project, I focused exclusively on labeling diagnostic images for use in computer vision model training. I followed documentation protocols to ensure that all boundary annotations were precise and audit-ready. My work contributed directly to the reliability of medical datasets used for evaluating AI models. • Annotated medical images using high-precision boundaries and expert-driven definitions. • Prioritized label consistency and accuracy for healthcare model applications. • Supported rigorous QA reviews to meet dataset compliance standards. • Ensured audit readiness and transparency for dataset handoff stages.

As part of a Medical Imaging AI Dataset Project, I focused exclusively on labeling diagnostic images for use in computer vision model training. I followed documentation protocols to ensure that all boundary annotations were precise and audit-ready. My work contributed directly to the reliability of medical datasets used for evaluating AI models. • Annotated medical images using high-precision boundaries and expert-driven definitions. • Prioritized label consistency and accuracy for healthcare model applications. • Supported rigorous QA reviews to meet dataset compliance standards. • Ensured audit readiness and transparency for dataset handoff stages.

2022 - Present

AI Data Annotation & QA Specialist (Contract / Project-Based)

CVATImageBounding Box

I served as an AI Data Annotation & QA Specialist focusing on detailed data labeling activities for machine learning projects. My responsibilities included labeling, reviewing, and ensuring the quality of image, text, and mixed-modal datasets. I worked under strict guidelines to consistently provide high-quality annotations for downstream AI model training. • Labeled and reviewed over 10,000 image, text, and medical data samples using quality assurance workflows. • Performed image annotation (bounding boxes, segmentation) and medical image labeling for clinical AI applications. • Applied reinforcement learning from human feedback (RLHF) techniques, conducted error audits, and delivered structured feedback. • Utilized tools like CVAT and Labelbox-style workflows while maintaining 98–99% annotation accuracy.

I served as an AI Data Annotation & QA Specialist focusing on detailed data labeling activities for machine learning projects. My responsibilities included labeling, reviewing, and ensuring the quality of image, text, and mixed-modal datasets. I worked under strict guidelines to consistently provide high-quality annotations for downstream AI model training. • Labeled and reviewed over 10,000 image, text, and medical data samples using quality assurance workflows. • Performed image annotation (bounding boxes, segmentation) and medical image labeling for clinical AI applications. • Applied reinforcement learning from human feedback (RLHF) techniques, conducted error audits, and delivered structured feedback. • Utilized tools like CVAT and Labelbox-style workflows while maintaining 98–99% annotation accuracy.

2022 - Present

Education

Work History