The Role
Design, develop, and optimize ETL pipelines and repositories for large-scale medical imaging (CT, MRI). Integrate with PACS/XNAT, extract and standardize DICOM/HL7/FHIR metadata, implement automated labeling/segmentation, and optimize AWS storage and retrieval for high-performance clinical applications.
Summary Generated by Built In
RapidAI is the trusted leader in deep clinical AI, helping hospitals deliver faster, more informed care through intelligent imaging and integrated workflows. The Rapid Enterprise™ Platform supports disease states across the care spectrum, but it’s our clinical depth that drives the most meaningful impact — improving decision-making, patient outcomes, and health-system performance. Used by more than 2,500 hospitals in over 100 countries and backed by 700+ clinical studies, including research that helped expand national stroke-treatment guidelines, RapidAI is the most clinically validated AI platform in healthcare.
What you will do:
Design, develop, and optimize ETL pipelines for large-scale medical imaging datasets, ensuring efficient data ingestion, transformation, and storage.
Build and maintain medical imaging data repositories, ensuring seamless access,
query optimization, and compliance with healthcare regulations.
Implement data processing workflows for clinical imaging data (CT, MRI) to extract,
standardize, and structure metadata.
Develop scalable solutions for medical imaging data engineering, integrating with
PACS or XNAT, and other imaging systems.
Apply computer vision and machine learning techniques to analyze and process
medical images for healthcare applications, linking imaging data with associated
clinical metadata.
Extract and standardize image metadata (DICOM headers, HL7, FHIR) for enhanced
image classification and retrieval.
Develop automated image labeling and segmentation workflows using metadata
driven insights.
Optimize data storage and retrieval on AWS (S3, Lambda, EC2, DynamoDB, Redshift) for
high-performance clinical applications.
What you will bring:
7 to 10 years of experience in data engineering with a focus on healthcare imaging and
medical imaging data.
Expertise in medical imaging standards (preferably DICOM, but familiarity with other
formats is valuable) and clinical metadata processing.
RapidAI is committed to creating an inclusive and diverse workplace. We provide equal employment opportunities to all employees and applicants and prohibit discrimination and harassment of any type in regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Skills Required
- 7 to 10 years of experience in data engineering with a focus on healthcare imaging and medical imaging data.
- Expertise in medical imaging standards (preferably DICOM) and clinical metadata processing.
- Experience designing and optimizing ETL pipelines for large-scale medical imaging datasets.
- Experience building and maintaining medical imaging repositories and integrating with PACS or XNAT.
- Experience extracting and standardizing image metadata (DICOM headers, HL7, FHIR).
- Experience optimizing data storage and retrieval on AWS (S3, Lambda, EC2, DynamoDB, Redshift).
- Experience applying computer vision and machine learning techniques to analyze and process medical images.
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The Company
What We Do
RapidAI is the global leader in using AI to combat life-threatening vascular and neurovascular conditions. Leading the next evolution of clinical decision-making and patient workflow, RapidAI is empowering physicians to make faster decisions for better patient outcomes. Based on intelligence gained from over 5 million scans in more than 2,000 hospitals in over 60 countries, the Rapid® platform transforms care coordination, offering care teams a level of patient visibility never before possible. RapidAI — where AI meets patient care.
