The Data Engineer will play a crucial role in developing and fine-tuning data specifically for our LLMs and machine learning models.

Requirements

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.

Benefits

Competitive salary and benefits package.
Flexible working arrangements (remote or hybrid options available).
The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

The Data Engineer will play a crucial role in developing and fine-tuning data specifically for our LLMs and machine learning models.

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.

Competitive salary and benefits package.
Flexible working arrangements (remote or hybrid options available).
The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.