Key Skills

Software

AWS SageMaker

CVAT

Data Annotation Tech

Scale AI

V7 Labs

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Image

Top Task Types

Classification

Data Collection

Fine-tuning

Freelancer Overview

I am a data annotation specialist with extensive experience creating, curating, and validating high-quality AI training datasets across text, image, audio, and code domains. My work spans designing labeling guidelines, using industry-standard tools such as Labelbox, CVAT, Prodigy, and SageMaker Ground Truth, and developing custom Python-based workflows for automation and quality assurance. I have a strong understanding of AI/ML pipelines, from raw data ingestion to model evaluation, ensuring that labeled datasets are consistent, scalable, and optimized for real-world performance. In past projects, I have led labeling efforts for natural language processing tasks such as named entity recognition and sentiment analysis, computer vision projects including object detection and semantic segmentation, and code intelligence tasks like function classification and dependency mapping. My strengths include maintaining high inter-annotator agreement, implementing gold-standard checks, and collaborating closely with engineering teams to integrate training data into production AI systems. This combination of technical skill, domain versatility, and attention to detail enables me to deliver datasets that directly enhance model accuracy and reliability.

Labeling Experience

Education

Work History