AI/ML Engineer-ICL-Open Rank (Entry-Junior Level)

About the role

The Georgia Tech Research Institute (GTRI) is seeking an AI/ML Engineer to join the Health Interoperability and Security Branch (HISB) within the Health Emerging & Advanced Technologies (HEAT) Division. HISB focuses on solving applied research problems in public health, particularly in the state of Georgia.

Responsibilities

• Develop software products using software tools such as R, Python, C++, C and/or Julia
• Deploy machine learning models utilizing existing tooling
• Conduct research in a multi-disciplined team environment
• Design and implement agentic AI systems that coordinate complex health data workflows across multiple systems and stakeholders
• Develop multi-agent AI architectures that can collaborate to solve complex health interoperability challenges
• Make a meaningful impact on health interoperability research by developing and deploying AI/ML solutions that enhance data exchange, integration, and standardization across disparate health systems
• Engage in health research by exploring literature in machine learning, artificial intelligence, and computer science to find innovative solutions for real-world health interoperability problems
• Develop and apply novel solutions to address research challenges, including the use of machine learning models, large language models, agentic AI systems, and workflow orchestration frameworks for tasks such as clinical data extraction, semantic interoperability, automated data quality assessment, data mapping, validation, and standards conversion
• Collaborate with fellow researchers in multidisciplinary research and review work for quality improvement
• Communicate verbal and written feedback in a clear and effective manner

Requirements

• Strong proficiency in Python
• Strong machine learning, artificial intelligence, computer science, or software engineering background
• Experience developing, deploying, or working with APIs and data exchange systems
• Experience communicating and presenting technical findings, both written and verbal
• Ability to work collaboratively in a multidisciplinary team environment

Preferred Qualifications

• Experience with AI workflow orchestration tools and frameworks (e.g., LangChain, LlamaIndex, Apache Airflow)
• Experience building agentic AI systems, autonomous workflows, or multi-agent architectures
• Experience implementing AI observability, monitoring, and evaluation frameworks for ML systems
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes)
• Experience with health interoperability standards and frameworks such as FHIR, HL7, DICOM, and healthcare terminologies (LOINC, SNOMED CT, ICD, RxNorm)
• Experience with version control systems (Git) and CI/CD practices for ML deployment
• Knowledge of data security, encryption, federated learning, differential privacy, or other privacy-enhancing technologies
• Experience with RESTful APIs, microservices architecture, and distributed systems