Dante Fabillar

Key Skills

Software

Appen

Labelbox

Lionbridge

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Geospatial Tiled Imagery

Image

Top Task Types

Action Recognition

Bounding Box

Classification

Computer Programming Coding

Object Detection

Freelancer Overview

I have over five years of hands-on experience in AI/ML data operations, specializing in human-in-the-loop data labeling, annotation, and quality assurance for projects with Appen, OneForma, and RYU Data Centre. My work spans multi-modal annotation including text, image, and audio data, with a strong focus on refining guidelines, ensuring inter-annotator agreement, and implementing rigorous QA sampling and feedback loops. I have contributed to computer vision projects such as 2D/3D residential and land-cover annotation, as well as NLP and audio transcription tasks for international clients. I am adept with annotation platforms and tools, and recognized for delivering high-quality, accurate datasets that drive model training and validation. My approach is detail-oriented and process-driven, ensuring compliance with project requirements and consistent, reliable results.

Labeling Experience

Audio Annotator/Transcriptor

AppenAudioClassification

As an Audio Annotator and Transcriptor, I transcribed audio recordings and classified various elements within them. This included sentiment analysis of speakers, background noise identification, and filtering out invalid sounds. My work contributed to large-scale annotation projects for English audio datasets. • Transcribed approximately 5 minutes of audio per assignment • Analyzed sentiment and background noise in recordings • Labeled invalid and unusable audio segments • Participated in projects for the 8K English Annotation Project via Appen and MatrixGo

As an Audio Annotator and Transcriptor, I transcribed audio recordings and classified various elements within them. This included sentiment analysis of speakers, background noise identification, and filtering out invalid sounds. My work contributed to large-scale annotation projects for English audio datasets. • Transcribed approximately 5 minutes of audio per assignment • Analyzed sentiment and background noise in recordings • Labeled invalid and unusable audio segments • Participated in projects for the 8K English Annotation Project via Appen and MatrixGo

2023

Image Annotator, Labeler & Quality Assurance Agent

LabelboxImageObject Detection

As an Image Annotator, Labeler, and Quality Assurance Agent, I was responsible for annotating and labeling images of persons and objects. My main tasks included judging, checking, and fixing labelers' outputs to ensure high-quality results in the final destination. I adapted quickly to various annotation tools and consistently maintained high accuracy. • Performed detailed image annotation using object detection techniques • Conducted quality assurance reviews on labeled datasets • Utilized platforms such as Labelbox, Supervisely, and Appen • Collaborated with international teams in Japan and Korea

As an Image Annotator, Labeler, and Quality Assurance Agent, I was responsible for annotating and labeling images of persons and objects. My main tasks included judging, checking, and fixing labelers' outputs to ensure high-quality results in the final destination. I adapted quickly to various annotation tools and consistently maintained high accuracy. • Performed detailed image annotation using object detection techniques • Conducted quality assurance reviews on labeled datasets • Utilized platforms such as Labelbox, Supervisely, and Appen • Collaborated with international teams in Japan and Korea

2022

Labeler and Rater

AppenImageEvaluation Rating

As a Labeler and Rater for Crescent UHRS, I labeled and rated various task types including images, text, audio, and search relevance. My responsibilities involved evaluating content across multiple data formats to support AI development and improvements. This role required attention to detail and an ability to adapt to quickly shifting project requirements. • Labeled and rated data for images, text, and audio • Performed relevance assessments for search-related tasks • Worked within the UHRS platform for content evaluation • Ensured data quality by verifying label accuracy

As a Labeler and Rater for Crescent UHRS, I labeled and rated various task types including images, text, audio, and search relevance. My responsibilities involved evaluating content across multiple data formats to support AI development and improvements. This role required attention to detail and an ability to adapt to quickly shifting project requirements. • Labeled and rated data for images, text, and audio • Performed relevance assessments for search-related tasks • Worked within the UHRS platform for content evaluation • Ensured data quality by verifying label accuracy

2018 - 2020

Education

Work History