AI Data Engineer

Position Summary The Data Engineer will play a crucial role in developing and fine-tuning data specifically for our LLMs and machine learning models. This individual will be responsible for the entire data lifecycle, including gathering, cleaning, structuring, and optimizing large, diverse healthcare datasets. The ideal candidate will have a strong background in data engineering principles, experience with big data technologies, and a keen understanding of the unique challenges and requirements of healthcare data. You will design, build, and maintain scalable data pipelines that source, preprocess, and deliver high-quality, high-volume datasets to our machine learning engineers. This role requires a deep understanding of data engineering best practices coupled with specific knowledge of the data requirements for LLM training and refinement Key Responsibilities Collaborate with data scientists and machine learning engineers to understand data requirements for LLM and machine learning model fine-tuning. Design, build, and maintain scalable data pipelines to ingest, process, and store massive and diverse healthcare datasets. Implement robust data validation and monitoring to ensure the integrity, accuracy, and consistency of all training datasets. Implement robust data cleaning, validation, and transformation processes to ensure data quality and integrity. Develop and optimize data structures and schemas for efficient access and utilization by LLMs and machine learning models. Work with the team to identify and acquire new data sources, ensuring compliance with relevant healthcare regulations (e.g., HIPAA). Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability. Document data engineering processes, data models, and data dictionaries. Stay up-to-date with the latest advancements in data engineering, big data technologies, and machine learning.