Health AI Engineer

The University of Minnesota’s Division of Computational Health Science (CHS) is seeking a Health AI Engineer to join a multidisciplinary team focused on health data science, biomedical informatics, and artificial intelligence. In this onsite role in Minneapolis, MN, you will design, build, test, and evaluate AI, machine learning, NLP, and generative AI solutions that support healthcare and biomedical research efforts, from computational experiments to scientific communication.

What you will do

• Design, implement, test, and evaluate AI, machine learning, NLP, generative AI, and data science methods for healthcare and biomedical research projects.
• Run computational experiments using EHR data, clinical text, and other structured and unstructured biomedical datasets.
• Create reproducible research pipelines, software tools, and AI systems that support research studies and help translate methods into usable solutions.
• Support new research projects through literature reviews, study design, data preparation, experimental design, and selection of appropriate analytical and AI methods.
• Evaluate AI systems using quantitative and qualitative methods, including assessment of accuracy, robustness, generalizability, reliability, and potential limitations.
• Analyze experimental results, troubleshoot technical issues, and recommend methodological or engineering improvements.
• Summarize findings and contribute to manuscripts, technical reports, presentations, posters, and grant proposals, along with other scientific outputs.
• Communicate analytical and technical results to faculty investigators, clinicians, research scientists, engineers, students, sponsors, and other collaborators.
• Collaborate within multidisciplinary research teams while independently managing assigned projects and deliverables.
• Work under general supervision with substantial latitude to determine technical approaches, prioritize activities, and make decisions within areas of responsibility.
• Maintain high-quality research code, documentation, data analysis workflows, and experimental records to support reproducibility and collaboration.
• Stay current with developments in health AI, generative AI, agentic systems, biomedical informatics, and related technologies, and assess potential application to ongoing research.

Required qualifications

• B.A./B.S. in Biomedical/Health Informatics, Data Science, Computer Science, Engineering, or a related quantitative/technical discipline, plus at least five years of relevant experience, or a combination of education and relevant work experience totaling at least nine years.
• Strong foundation in algorithms, data structures, software engineering principles, and computational methods.
• Strong programming skills in Python and/or Java; experience with SQL and familiarity with C/C++ or other programming languages.
• Ability to demonstrate programming proficiency through prior projects or sample code.
• Understanding of healthcare data, biomedical data, and common health AI and informatics applications.
• Experience developing, implementing, testing, and evaluating data science, machine learning, or AI solutions.
• Ability to work independently, manage assigned research and engineering tasks, and adapt to a rapidly evolving scientific and technical environment.

Preferred qualifications

• Research or applied experience in health data science, biomedical informatics, artificial intelligence, and real-world health data analytics.
• Experience working with electronic health record (EHR) data, clinical text, or other large-scale biomedical datasets.
• Knowledge of medical terminologies and ontologies, such as UMLS, SNOMED CT, ICD, RxNorm, or related standards.
• Experience with natural language processing, large language models (LLMs), generative AI, retrieval-augmented generation (RAG), and/or agentic AI systems.
• Experience evaluating AI systems, including assessment of model performance, robustness, generalizability, and reliability in healthcare applications.
• Experience contributing to scientific publications, conference presentations, technical reports, or research proposals.
• Ability to collaborate effectively with multidisciplinary teams of faculty, clinicians, research scientists, engineers, students, and other research professionals.

Technologies and data

• Python, Java, SQL, C/C++, NLP, generative AI, large language models (LLMs), retrieval-augmented generation (RAG), agentic AI systems
• EHR data, UMLS, SNOMED CT, ICD, RxNorm

Department and appointment details

• The Division of Computational Health Science (CHS) is seeking a master’s level data scientist for a multidisciplinary team.
• This is an annually renewable professional academic appointment.
• CHS develops and applies innovative data science and AI methods to analyze complex biomedical and healthcare data, supporting biomedical research, clinical care, and learning health systems.
• The Natural Language Processing / Information Extraction (NLP/IE) Program brings together faculty investigators, research scientists, engineers, postdoctoral researchers, programmers, and students to develop and evaluate NLP and AI methods for clinical and biomedical applications.
• Current and emerging areas include clinical NLP, large language models, generative AI, agentic AI, retrieval-augmented generation, real-world data analytics, and trustworthy health AI.

How to apply

• Applications must be submitted online, with the opportunity to attach a cover letter and resume.
• Additional documents may be attached after application by using “My Job Applications” and uploading documents in the “My Cover Letters and Attachments” section.
• To request an accommodation during the application process, email [email protected].
• The University recognizes and values diversity and inclusion.
• Any offer of employment is contingent upon successful completion of a background check.