AI​/ML Engineer - GTRI-ICL

Overview

Georgia Tech Research Institute (GTRI) is the nonprofit, applied research division of the Georgia Institute of Technology. Founded in 1934 as the Engineering Experiment Station, GTRI has grown to more than 2,900 employees, supporting eight laboratories in over 20 locations around the country and performing more than $940 million of problem‑solving research annually for government and industry. GTRI’s renowned researchers combine science, engineering, economics, policy, and technical expertise to solve complex problems for the U.S. federal government, state, and industry.

• Students are our top priority.
• We strive for excellence.
• We thrive on diversity.
• We celebrate collaboration.
• We champion innovation.
• We safeguard freedom of inquiry and expression.
• We nurture the wellbeing of our community.
• We act ethically.
• We are responsible stewards.

The Health Emerging & Advanced Technologies (HEAT) Division is dedicated to improving individual and population health through advances in the capture, analysis, and standards‑based, interoperable communication of health data. Our goals are: (1) to advance foundational technologies in health data analytics; (2) to promote interoperability and open‑source platforms in health; (3) to support health‑care partners in maximizing the value of their data resources;

and (4) to foster scalable and secure health research locally and globally.

The Health Analytics and Phenotyping Branch (HAPB) in the HEAT Division is dedicated to solving applied research problems in public health, both nationally and specifically in the state of Georgia. Data scientists in HAPB employ data science solutions to improve health outcomes and inform policy decisions. The branch focuses on leveraging big data, data visualization, artificial intelligence, and statistical methods to: (1) identify and analyze health trends;

(2) support health decision making; and (3) enhance disease surveillance.

The AI/ML Engineer develops AI/ML algorithms, cloud computing, and/or heterogeneous distributed computing infrastructures to support the deployment of AI/ML applications. The engineer also researches the mathematical foundations and frameworks for nonlinear systems characterized by time‑varying and emerging dynamics of evolving or adaptive systems. They develop technical solutions at the leading edge of Artificial Intelligence, Machine Learning, Genetic Programming, Computer Vision, and advanced data processing, filtering, and fusion techniques in high‑performance computing and distributed heterogeneous computing environments.

The engineer writes parallel processing programs to deploy ML models developed by data scientists into more complex systems and leverages the most recent advances in statistical analysis of large data sets to advance state‑of‑the‑art automated sensor and data processing for a broad range of intelligent and sensor‑enabled systems.

• Develop software products using 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.

• Make a meaningful impact on health research by preparing data, running and tuning machine learning models, analyzing longitudinal trends, performing statistical analyses, building data visualizations, and communicating findings.
• Uncover important trends from data by integrating data from multiple sources, ensuring data quality, and managing metadata.
• Engage in health research by exploring literature in machine learning, artificial intelligence, computer science, statistics, and mathematics to find innovative solutions for real‑world health research problems.
• Develop and apply novel solutions to address health research challenges, including the use of machine learning models, statistical models, large language models, and other AI‑centered tools.
• Collaborate with fellow researchers in multidisciplinary research and review work for quality improvement.

• Strong proficiency in Python and SQL.
• Strong machine learning, artificial intelligence,…