Israel M.

Key Skills

Software

Labelbox

CVAT

SuperAnnotate

Other

Top Subject Matter

Computer Vision (Image Annotation)

Text Classification (Intent/Sentiment Tagging)

Audio Dataset Annotation

Top Data Types

Image

Text

Audio

Top Task Types

Bounding Box

Classification

Transcription

Freelancer Overview

Freelance Data Labeler (Remote). Core strengths include Labelbox, CVAT, and SuperAnnotate. Education includes Diploma / Certificate, N/A. AI-training focus includes data types such as Image, Text, and Audio and labeling workflows including Bounding Box, Classification, and Transcription.

Labeling Experience

Freelance Data Labeler (Remote) - Audio Labeling

OtherAudioTranscription

Annotated audio clips as part of machine learning dataset preparation while adhering to strict labeling guidelines. Maintained consistent labeling quality and performed manual reviews to ensure correctness and usefulness for model training. Delivered high-quality outputs intended to improve overall dataset clarity and model performance. • Labeled audio clips for ML dataset requirements. • Followed structured annotation instructions closely. • Performed manual reviews for quality assurance. • Reported 98%+ labeling accuracy across delivered work.

2023 - Present

Text Classification Project / Freelance Text Labeling

LabelboxTextClassification

Labeled textual data by tagging sentences with intents, sentiment, and relevance categories for ML training. Followed annotation standards to produce consistent labels across examples and support text classification workflows. Performed dataset verification activities to maintain label accuracy and reduce ambiguity. • Tagged sentences by intent, sentiment, and relevance. • Produced consistent text labels for machine learning model training. • Supported quality assurance through manual reviews. • Refined/clarified annotation instructions to improve dataset consistency.

2023 - Present

Freelance Data Labeler (Remote)

LabelboxImageBounding Box

Freelance Data Labeler responsible for annotating image datasets to support machine learning training workflows. Labeled objects using bounding boxes and refined polygon annotations in line with structured guidelines. Performed manual reviews to maintain labeling consistency and accuracy throughout the dataset lifecycle.• Annotated 5,000+ images with bounding boxes and polygons.• Followed strict annotation instructions to achieve 98%+ accuracy.• Conducted quality assurance checks and dataset verification.• Supported improvements in object detection model performance.

2023 - Present

Education

Work History