Team A-TEK is looking to improve the processing and interoperability of federal electronic health records (EHR) data by designing, developing, and maintaining AI/ML models.
Requirements
- Proficiency with AWS SageMaker, MLflow, and Natural Language Processing (NLP) tools.
- Experience working with FHIR, OMOP, HL7 standards, and federal EHR data systems.
- Knowledge of HIPAA, FedRAMP High, and FISMA compliance requirements.
- Minimum of 3 years of hands-on experience in ML/AI model development.
Responsibilities
- Design, build, train, and deploy machine learning models tailored for healthcare interoperability and health data analytics.
- Develop AI-driven solutions for schema mapping, patient record linkage, anomaly detection, and predictive modeling for public health applications.
- Apply healthcare data standards such as FHIR, OMOP, and HL7 to integrate federal EHR systems securely and efficiently.
- Support tokenization and privacy-preserving record linkage techniques to ensure data security and compliance.
- Optimize model performance, accuracy, and interpretability through continuous monitoring and iterative improvements.
- Implement and adhere to model governance frameworks, maintaining documentation for audit readiness and compliance.
- Collaborate with cross-functional teams to ensure seamless data ingestion, interoperability, and secure data exchange.
Other
- Ability to obtain and maintain a Public Trust Level 4 clearance.
- Occasional travel to McLean, VA.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
