About the role#
The American Heart Association is seeking an intern to support the Data Science team. This role focuses on machine learning and artificial intelligence, specifically large language models (LLMs), generative AI, and agentic AI. You will build foundational knowledge of how LLMs function and apply them to modeling, analytical workflows, and research use cases. Working alongside data scientists and cross-functional partners, you will help develop reproducible AI-enabled workflows and learn to evaluate, validate, and document solutions for clinical and biomedical research settings.
What you'll do#
- Support the design and development of LLM-powered applications and agentic AI workflows for clinical, biomedical, and operational research.
- Apply LLMs to modeling and analytical tasks such as information extraction, classification, summarization, question answering, and workflow orchestration.
- Experiment with prompt design, structured outputs, retrieval-augmented generation, embeddings, vector search, tool use, and multi-step agent workflows.
- Prepare, clean, organize, and document data used in LLM and generative AI experiments.
- Develop reproducible prototypes and workflows using Python and approved AI/ML tools.
- Design and perform evaluations of LLM systems using quantitative and qualitative measures.
- Conduct validation, error analysis, robustness testing, and comparison of model or workflow alternatives.
- Assess issues including hallucination, factual consistency, relevance, reliability, bias, privacy, and reproducibility.
- Document methods, assumptions, prompts, evaluation results, limitations, and recommended improvements.
- Contribute to technical documentation, presentations, abstracts, manuscripts, and project discussions.
What you'll need#
- Currently pursuing an MS or PhD in Computer Science, Artificial Intelligence, Biomedical Informatics, Data Science, Statistics, Engineering, Public Health, or a related quantitative field.
- Coursework or project experience with LLMs, generative AI, natural language processing, retrieval-augmented generation, or AI agents.
- Experience using APIs or open-source frameworks to build and test LLM applications.
- Programming experience in Python and familiarity with common data analysis or machine learning libraries.
- Ability to understand and apply core LLM concepts such as tokens, context windows, embeddings, prompting, retrieval, and generation.
- Strong analytical, problem-solving, organizational, and attention-to-detail skills.
- Commitment to reproducible research, responsible AI practices, data quality, and clear documentation.
- Ability to communicate effectively and collaborate with technical and non-technical colleagues.
- Experience working with cloud computing or high-performance computing environments (e.g., AWS, Snowflake, Azure, GCP).
- Familiarity with model evaluation, experimental design, error analysis, version control, or reproducible workflow practices.
- Intermediate to excellent proficiency in Microsoft Word, Excel, Outlook, and PowerPoint.
- Experience with healthcare, clinical, or biomedical datasets is preferred.
- Must be legally authorized to work in the United States without sponsorship.
Location & details#
- Term: Winter 2027 (January 25, 2027, to May 7, 2027).
- Modality: Remote.
- Compensation: $23.00 per hour.
- Availability: Minimum of 20 hours per week, Monday through Friday, between 8:30am and 5:00pm.
- Equipment: Reliable WiFi connection required.
About American Heart Association
The American Heart Association is a nonprofit organization focused on cardiovascular health. Founded in 1924, it functions as the oldest and largest voluntary organization in the United States dedicated to fighting heart disease and stroke. The group funds research, provides professional education, and advocates for policy changes. It employs over 11,000 people and maintains its headquarters in Dallas, Texas.
How to get in at American Heart Association
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