Patricia Clark

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Top Label Types

Bounding Box

Point Key Point

Segmentation

Classification

Tracking

Action Recognition

Freelancer Overview

I am an AI training specialist with 4 years of hands-on experience in data labeling and annotation for images, videos, and audio, supporting machine learning, computer vision, and speech recognition projects. My expertise includes performing precise bounding box, polygon, keypoint, and segmentation annotations, as well as frame-by-frame video annotation and object tracking. I am skilled in using industry-standard tools like Labelbox, YOLO, and various audio and video annotation platforms, always maintaining accuracy and strict adherence to annotation guidelines. I take pride in delivering high-quality, consistent datasets that enhance model performance, and I enjoy collaborating with QA teams to ensure data integrity. I am open to remote and contract opportunities where I can contribute my attention to detail and passion for building robust AI training data.

Labeling Experience

Video Data Annotation for Object Detection & Tracking

LabelboxVideoBounding BoxPoint Key Point

Performed frame-by-frame video annotation for computer vision and AI model training. Responsibilities included labeling moving objects using bounding boxes and polygons, applying segmentation masks, and maintaining consistent object IDs for tracking across video sequences. Supported action recognition tasks by accurately labeling object behavior and motion over time. Ensured high-quality annotations through strict adherence to guidelines, validation checks, and collaboration with quality assurance teams.

Performed frame-by-frame video annotation for computer vision and AI model training. Responsibilities included labeling moving objects using bounding boxes and polygons, applying segmentation masks, and maintaining consistent object IDs for tracking across video sequences. Supported action recognition tasks by accurately labeling object behavior and motion over time. Ensured high-quality annotations through strict adherence to guidelines, validation checks, and collaboration with quality assurance teams.

2024

Computer Vision Data Annotation for Object Detection & Tracking

LabelboxImageBounding BoxPoint Key Point

Annotated large-scale image datasets for computer vision and machine learning applications. Tasks included drawing bounding boxes, polygons, and key points for object detection and classification, as well as pixel-level segmentation for model accuracy. Ensured high-quality annotations by strictly following project guidelines and performing self-QA checks. Contributed to improving model performance through consistent and accurate labeling across diverse image datasets.

Annotated large-scale image datasets for computer vision and machine learning applications. Tasks included drawing bounding boxes, polygons, and key points for object detection and classification, as well as pixel-level segmentation for model accuracy. Ensured high-quality annotations by strictly following project guidelines and performing self-QA checks. Contributed to improving model performance through consistent and accurate labeling across diverse image datasets.

2022 - 2024

Education

Work History