AI/ML Engineer - GTRI-ICL

Overview: The Georgia Tech Research Institute (GTRI) is the nonprofit, applied research division of the Georgia Institute of Technology (Georgia Tech). 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. Georgia Tech's Mission and Values Georgia Tech's mission is to develop leaders who advance technology and improve the human condition. The Institute has nine key values that are foundational to everything we do: 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. Over the next decade, Georgia Tech will become an example of inclusive innovation, a leading technological research university of unmatched scale, relentlessly committed to serving the public good; breaking new ground in addressing the biggest local, national, and global challenges and opportunities of our time; making technology broadly accessible; and developing exceptional, principled leaders from all backgrounds ready to produce novel ideas and create solutions with real human impact. Project/Unit Description 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 healthcare 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. This 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. Job Purpose The Artificial Intelligence/Machine Learning (AI/ML) Engineer develops AI/ML algorithms, cloud computing, and/or heterogeneous distributed computing infrastructures to support the deployment of AI/ML applications. The AI/ML Engineer also researches the mathematical foundations and frameworks for nonlinear systems characterized by time‑varying and emerging dynamics of evolving or adaptive systems. The AI/ML Engineer develops 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 AI/ML Engineer writes parallel processing programs to deploy ML models developed by data scientists into more complex systems. The AI/ML Engineer has familiarity with state‑of‑the‑art, open‑source software frameworks and high‑performance computing accelerators for machine learning. When conducting research, the AI/ML Engineer 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. Key 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. Additional Responsibilities 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. This includes research projects utilizing claims, observational data, images, survey, and other types of data. Uncover important trends from data by integrating data from multiple sources, ensuring data quality, and managing metadata. Utilize linked data sets to better understand public health findings, longitudinal trends, geospatial factors, health disparities and demographic trends. 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. Communicate verbal and written feedback in a clear and effective manner. Required Minimum Qualifications Strong proficiency in Python and SQL. Strong machine learning, artificial intelligence, statistics, computer science, or data analytics background. Experience accessing and analyzing diverse data sets, including flat files (i.e. CSVs), APIs, and relational databases (i.e. Postgres). Experience in performing analytical tasks with data including machine learning, statistical methods and data visualization. Experience communicating and presenting data findings, both written and verbal. Preferred Qualifications Experience analyzing health data, including but not limited to claims data, images, electronic medical record data, and public health survey data. Experience running and tuning models for natural language processing, LLMs, VLMs, and other AI tools. Experience gathering and cleaning data from the web via APIs and other web scraping techniques. Strong experience with Python libraries, including but not limited to pandas, numpy, matplotlib, etc. Experience with R and Shiny. Experience working with sensitive health care data (PHI/PII) and secure environments. Experience building data visualizations with Tableau and Power BI. Experience using analytical skills to perform population‑level estimation and patient‑level prediction. Familiarity with clinical data standards including LOINC, SNOMED, etc. Travel Requirements Education and Length of Experience Levels 1+2 This position vacancy is an open‑rank announcement. The final job offer will be dependent on candidate qualifications in alignment with Research Faculty Extension Professional ranks as outlined in section 3.2.1 of the Georgia Tech Faculty Handbook. 0 years of related experience with a Bachelor's degree in Statistics, Computer Science, Data Analytics, Applied Mathematics. U.S. Citizenship Requirements Due to our research contracts with the U.S. federal government, candidates for this position must be U.S. Citizens. Clearance Type Required None Benefits at GTRI Comprehensive information on currently offered GTRI benefits, including Health & Welfare, Retirement Plans, Tuition Reimbursement, Time Off, and Professional Development, can be found through this link: Equal Employment Opportunity The Georgia Institute of Technology (Georgia Tech) is an Equal Employment Opportunity Employer. The Institute is committed to maintaining a fair and respectful environment for all. To that end, and in accordance with federal and state law, Board of Regents policy, and Institute policy, Georgia Tech provides equal opportunity to all faculty, staff, students, and all other members of the Georgia Tech community, including applicants for admission and/or employment, contractors, volunteers, and participants in institutional programs, activities, and services. Georgia Tech complies with all applicable laws and regulations governing equal opportunity in the workplace and in educational activities. Equal opportunity and decisions based on merit are fundamental values of the University System of Georgia (“USG”) and Georgia Tech. Georgia Tech prohibits discrimination, including discriminatory harassment, on the basis of an individual’s race, ethnicity, ancestry, color, religion, sex (including pregnancy), national origin, age, disability, genetics, or veteran status in its programs, activities, employment, and admissions. Further, Georgia Tech prohibits citizenship status, immigration status, and national origin discrimination in hiring, firing, and recruitment, except where such restrictions are required in order to comply with law, regulation, executive order, or Attorney General directive, or where they are required by Federal, State, or local government contract. #J-18808-Ljbffr Georgia Tech Research Institute