Key Skills

Software

AWS SageMaker

Clickworker

Google Cloud Vertex AI

Label Studio

OneForma

Telus

Internal/Proprietary Tooling

Top Subject Matter

Chatbot training

Text annotation (entity recognition, sentiment)

Image classification, Object detection and segmentation

Top Data Types

Computer Code Programming

Image

Text

Top Label Types

Computer Programming Coding

Data Collection

Object Detection

Polygon

Question Answering

Freelancer Overview

I have over three years of experience in data labeling and AI training, specializing in creating high-quality datasets that drive the performance of machine learning models. My expertise includes annotation for computer vision, natural language processing (NLP), and audio data across industries such as healthcare, e-commerce, and autonomous systems. I have a proven track record of managing large-scale labeling projects, ensuring accuracy, consistency, and efficiency through robust quality control measures and advanced labeling tools.

Labeling Experience

Data Labeling Specialist

Label StudioComputer Code ProgrammingSegmentationObject Detection

The project involved labeling and categorizing code snippets, functions, and modules to train an AI model for understanding and generating code structures. The primary goal was to help developers by enabling automated suggestions, improving searchability, and assisting in code comprehension tools. My role included analyzing large repositories of source code in various programming languages such as Python, Java, and C++, and annotating the following: Code Snippets - Highlighting reusable code blocks and categorizing them by functionality (e.g., sorting algorithms, database queries). Functions - Annotating function definitions with their purpose, parameters, and return types. Modules - Identifying and categorizing modules or libraries based on their utility, such as data processing, networking, or UI design.

The project involved labeling and categorizing code snippets, functions, and modules to train an AI model for understanding and generating code structures. The primary goal was to help developers by enabling automated suggestions, improving searchability, and assisting in code comprehension tools. My role included analyzing large repositories of source code in various programming languages such as Python, Java, and C++, and annotating the following: Code Snippets - Highlighting reusable code blocks and categorizing them by functionality (e.g., sorting algorithms, database queries). Functions - Annotating function definitions with their purpose, parameters, and return types. Modules - Identifying and categorizing modules or libraries based on their utility, such as data processing, networking, or UI design.

2021 - 2024

Education

Work History