Adam Troy

Key Skills

Software

AWS SageMaker

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Text Summarization

Fine Tuning

Freelancer Overview

With over 15 years of experience in AI architecture and data engineering, I have a strong background in designing and implementing scalable data platforms to support advanced AI and machine learning workflows. My work has involved building and optimizing large-scale data pipelines, developing microservices for real-time data ingestion, and collaborating with cross-functional teams to ensure high-quality, well-annotated training datasets for AI models. I am skilled in Python, Java, and Scala, and have extensive experience deploying machine learning solutions on cloud platforms such as Google Cloud Vertex AI and AWS. My expertise includes integrating large language models (LLMs) with frameworks like RAG and LangChain, as well as ensuring robust data governance, compliance, and ethical AI practices. I am passionate about leveraging high-quality data annotation and labeling to drive intelligent, reliable AI systems across diverse domains.

Labeling Experience

AI/ML Data Annotation & LLM Training Pipeline Development

Aws SagemakerTextText SummarizationFine Tuning

Designed and ran data pipelines and annotation workflows that were used to train and test AI and machine learning models, such as Large Language Models (LLMs) and autonomous agent systems. Created scalable data labeling systems for entity recognition, semantic tagging, and text classification to help AI-powered decision support platforms. Worked with teams from different departments to make sure that the annotated datasets were of high quality and met the needs of model training. Used AWS and Google Cloud Vertex AI to set up a cloud-based data infrastructure that makes it easier to prepare, validate, and deploy datasets. We made sure that labeled training datasets were accurate, reliable, and compliant by using strict quality control measures, data governance policies, and ethical AI guidelines. The labeled datasets helped enterprise AI systems do predictive analytics, automation, and smart decision-making in a number of different fields.

Designed and ran data pipelines and annotation workflows that were used to train and test AI and machine learning models, such as Large Language Models (LLMs) and autonomous agent systems. Created scalable data labeling systems for entity recognition, semantic tagging, and text classification to help AI-powered decision support platforms. Worked with teams from different departments to make sure that the annotated datasets were of high quality and met the needs of model training. Used AWS and Google Cloud Vertex AI to set up a cloud-based data infrastructure that makes it easier to prepare, validate, and deploy datasets. We made sure that labeled training datasets were accurate, reliable, and compliant by using strict quality control measures, data governance policies, and ethical AI guidelines. The labeled datasets helped enterprise AI systems do predictive analytics, automation, and smart decision-making in a number of different fields.

2019 - 2024

Education

Work History