Anton Ferrolino

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Top Label Types

Bounding Box

Polygon

Point Key Point

Segmentation

Cuboid

Freelancer Overview

I am a highly organized and detail-oriented professional with hands-on experience in data labeling, annotation, and AI training data projects. My work at Remotasks in Modular Quality Assurance and as a Data Analyst at Outlier has given me a strong foundation in ensuring data accuracy and quality for machine learning models. I am skilled at working in fast-paced environments, managing multiple tasks efficiently, and quickly adapting to new tools and guidelines. I excel in maintaining confidentiality, meeting deadlines, and collaborating with teams to deliver high-quality annotated datasets for various domains. My analytical mindset and commitment to continuous learning allow me to contribute effectively to any data-driven project.

Labeling Experience

Data Annotation

Scale AI3D SensorBounding BoxPolygon

Responsible for performing precise 3D data annotation using LiDAR point clouds and 3D imagery to support the development of machine learning and artificial intelligence models. Tasks include accurately identifying, labeling, and classifying objects such as vehicles, pedestrians, road structures, and environmental elements within a 3D space. Ensures strict adherence to project guidelines, quality standards, and accuracy requirements while maintaining consistency across datasets. Demonstrates strong attention to detail, spatial awareness, and the ability to learn and apply new annotation tools effectively in a remote work environment.

Responsible for performing precise 3D data annotation using LiDAR point clouds and 3D imagery to support the development of machine learning and artificial intelligence models. Tasks include accurately identifying, labeling, and classifying objects such as vehicles, pedestrians, road structures, and environmental elements within a 3D space. Ensures strict adherence to project guidelines, quality standards, and accuracy requirements while maintaining consistency across datasets. Demonstrates strong attention to detail, spatial awareness, and the ability to learn and apply new annotation tools effectively in a remote work environment.

2019 - 2025

Education

Work History