Jennifer Leon

Key Skills

Software

CVAT

Dataloop

Labelbox

Remotasks

Roboflow

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Text

Top Task Types

Bounding Box

Cuboid

Polygon

Freelancer Overview

I’m a data annotation specialist with experience in AI projects focused on computer vision. I’ve worked with tools like CVAT, Labelbox 2D, Dataloop, and DriveX, performing bounding box, polygon, and image segmentation tasks in contexts such as boxed products, agricultural crops, and top-view drone imagery. My approach blends technical precision, standard compliance, and a clear understanding of AI training goals. I’ve also taken on coaching and leadership roles, guiding trainees on platforms like Remotasks and leading onboarding, technical validation, and quality control at Woflow, where I advanced from Data Specialist to Pod Leader. This growth reflects my ability to combine technical expertise with collaborative leadership, effective communication, and the creation of visual resources that enhance remote and multicultural workflows

Labeling Experience

computer vision project in the automotive sector, performing 3D LiDAR annotations for vehicles

Scale AI3D SensorCuboid

I contributed to a computer vision project in the automotive sector, performing 3D LiDAR annotations for vehicles. The goal was to create high-quality datasets to train AI models for detecting, classifying, and tracking cars in three-dimensional environments. My role focused on ensuring accuracy in object delimitation and consistency in labeling, supporting the development of advanced solutions for autonomous mobility and driver assistance systems.

I contributed to a computer vision project in the automotive sector, performing 3D LiDAR annotations for vehicles. The goal was to create high-quality datasets to train AI models for detecting, classifying, and tracking cars in three-dimensional environments. My role focused on ensuring accuracy in object delimitation and consistency in labeling, supporting the development of advanced solutions for autonomous mobility and driver assistance systems.

2024 - 2024

Polygon labeling of boxed items, like Amazon products

Scale AIVideoPolygon

I contributed to a computer vision project in the e‑commerce sector, performing polygon annotations on images of boxed items, similar to Amazon products. The goal was to build high‑quality datasets to train AI models capable of recognizing and classifying packaged goods, enhancing product identification and selection processes in online retail platforms. My role focused on ensuring labeling accuracy and data consistency, supporting the development of technological solutions for the retail industry.

I contributed to a computer vision project in the e‑commerce sector, performing polygon annotations on images of boxed items, similar to Amazon products. The goal was to build high‑quality datasets to train AI models capable of recognizing and classifying packaged goods, enhancing product identification and selection processes in online retail platforms. My role focused on ensuring labeling accuracy and data consistency, supporting the development of technological solutions for the retail industry.

2024 - 2024

Bounding Boxes for agaves by Citadelta

CVATImageBounding Box

At Citadelta Innovación, I contributed to a computer vision project in the agricultural sector by performing bounding box annotations on agave images. The goal was to create high-quality datasets to train AI models capable of identifying and classifying crops from drone-captured aerial imagery. My role focused on ensuring accuracy in item delimitation and consistency in labeling, supporting the development of technological solutions to optimize agricultural processes.

At Citadelta Innovación, I contributed to a computer vision project in the agricultural sector by performing bounding box annotations on agave images. The goal was to create high-quality datasets to train AI models capable of identifying and classifying crops from drone-captured aerial imagery. My role focused on ensuring accuracy in item delimitation and consistency in labeling, supporting the development of technological solutions to optimize agricultural processes.

2024 - 2024

Polygon annotation for a nutrition app project

Scale AIImagePolygon

I contributed to the development of a nutrition application by performing polygon annotations on food product images. The goal was to build high-quality datasets to train AI models capable of recognizing and classifying foods within the app, supporting product selection and nutritional recommendations. My role focused on ensuring accuracy in item delimitation and consistency in labeling, contributing to the training of computer vision systems applied to the health and nutrition sector.

I contributed to the development of a nutrition application by performing polygon annotations on food product images. The goal was to build high-quality datasets to train AI models capable of recognizing and classifying foods within the app, supporting product selection and nutritional recommendations. My role focused on ensuring accuracy in item delimitation and consistency in labeling, contributing to the training of computer vision systems applied to the health and nutrition sector.

2023 - 2024

Education

Work History