Tiffany P.

Key Skills

Software

Labelbox

CVAT

LabelImg

SuperAnnotate

Other

Top Subject Matter

Computer Vision (Object Detection, Segmentation, Object Tracking) and Multimedia Dataset Annotation

AI Training Dataset Labeling (Multimedia: Images, Audio, Video)

Top Data Types

Image

Video

Audio

Top Task Types

Object Detection

Segmentation

Tracking

Classification

Freelancer Overview

AI Data Annotation Specialist (Remote AI Training Projects). Core strengths include Labelbox, CVAT, and LabelImg. Education includes Bachelor of Science, University of Texas at Dallas (2017). AI-training focus includes data types such as Image, Video, and Audio and labeling workflows including Object Detection, Segmentation, and Tracking.

Labeling Experience

AI Data Annotation Specialist (Remote AI Training Projects)

LabelboxImageObject DetectionSegmentation

Annotated images and video frames to support computer vision model training and evaluation for object detection and segmentation tasks. Applied bounding box and segmentation labeling and performed object tracking annotation across video datasets while validating annotation accuracy against dataset guidelines. Ensured labeled multimedia data quality for downstream machine learning workflows. • Used Labelbox, CVAT, LabelImg, VGG Image Annotator (VIA), SuperAnnotate for labeling. • Labeled object detections with bounding boxes and segmentation labels. • Performed tracking annotations across video datasets. • Verified label consistency and high-quality dataset preparation using validation practices.

2022 - 2024

Multimedia Data Labeling Specialist (AI Dataset Projects)

OtherImageClassificationSegmentation

Labeled large-scale image, audio, and video datasets used for AI training and voice recognition. Tagged speech and sound events and organized datasets according to detailed annotation guidelines for model development. Performed object detection labeling and prepared structured training data for machine learning pipelines. • Tagged audio and speech events for voice recognition models. • Annotated images for object detection tasks with bounding boxes/labels. • Organized training datasets and followed annotation instructions. • Supported dataset preparation and quality through guideline adherence.

2018 - 2022

Education

Work History