Bill K.

Key Skills

Software

Appen

Data Annotation Tech

Labelbox

Mercor

Micro1

Snorkel AI

Argilla

Mindrift

Top Subject Matter

Artificial Intelligence – AI Model Training and Data Processing

Artificial Intelligence – Machine Learning Training and Testing

Artificial Intelligence – AI Systems Training and Improvement

Top Data Types

Image

Video

Computer Code Programming

Top Task Types

Classification

Polygon

Evaluation/Rating

Text Generation

Object Detection

Bounding Box

Segmentation

Entity (NER) Classification

Text Summarization

Question Answering

Computer Programming/Coding

Data Collection

Prompt + Response Writing (SFT)

Freelancer Overview

I have extensive experience in software engineering, architecture, and AI-related data work, and I’ve built my career around combining technical depth with leadership and research. As a Sr. Manager of Software Engineering at OpenText and previously a Principal Software Architect and Cloud Systems Architect, I’ve led teams in designing and integrating cloud-native systems, IoT solutions, and enterprise applications using technologies like AWS, Docker, Kubernetes, Node.js, Java, and modern frameworks. My Ph.D. research, MISFIT: Mining Software Fault Information and Types, gave me hands-on expertise in software fault classification, data analysis, and automation—skills that directly translate into AI training data and labeling. I’ve published multiple papers and hold patents in this area, which demonstrate my ability to design systems that classify, structure, and improve data quality. I also teach Computer Science Senior Design at the University of Kentucky, where I mentor students on applying industry practices to real-world projects. This role has strengthened my ability to translate complex technical concepts into structured training and data workflows, a skill that is highly relevant to AI training. I bring a unique combination of cloud architecture expertise, academic research in fault/data classification, and leadership in software engineering, which makes me a strong fit for roles involving AI training data, labeling, and automation.

Labeling Experience

Ph.D. Student / Research Assistant

ImageClassification

Conducted doctoral-level research and served as a research assistant while advancing software fault analysis methods. Completed dissertation defense covering MiSFIT: Mining Software Fault Information and Types. Applied rigorous research methodology, software engineering analysis, and scholarly communication skills. • Performed advanced research in software fault information and classification • Conducted analysis and validation for mined fault types • Wrote and presented academic findings and research summaries • Managed research activities through the dissertation timeline

2001 - 2015

Education

Work History