Intern, Data Science, Machine Learning, AI

American Heart Association

. Support the design and development of LLM-powered applications and agentic AI workflows for clinical, biomedical, and operational research use cases .

Posted 9/21/2026part-timeRemote • Texas • United StatesEntry Level💰 $23 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in LLM-powered application development, including prompt design, data preparation, and model evaluation. Proficient in Python programming and familiar with AI/ML tools, with a strong commitment to reproducible research and effective communication in cross-functional teams.

Highest-signal resume keywords

LLM Application DevelopmentPython ProgrammingNatural Language ProcessingData Preparation and DocumentationCloud Computing Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM ConceptsInformation ExtractionClassificationSummarizationQuestion AnsweringWorkflow OrchestrationError AnalysisRobustness TestingData Analysis LibrariesExperimental Design

Soft Skills

Analytical SkillsProblem-SolvingOrganizational SkillsAttention to DetailEffective Communication

Tools & Technologies

AWSSnowflakeAzureGCPMicrosoft WordMicrosoft ExcelMicrosoft OutlookMicrosoft PowerPoint

Industry Keywords

Biomedical InformaticsClinical ResearchGenerative AIHealthcare DatasetsResponsible AI Practices

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Support the design and development of LLM-powered applications and agentic AI workflows for clinical, biomedical, and operational research use cases
Apply LLMs to modeling and analytical tasks, including 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 and platforms
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 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 cross-functional project discussions

Requirements

What you’ll need

Currently pursuing an MS or PhD degree 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 both technical and non-technical colleagues
Experience working with cloud computing and/or high-performance computing environments, such as AWS, Snowflake, Azure, or GCP
Familiarity with model evaluation, experimental design, error analysis, version control, or reproducible workflow practices
Experience with healthcare, clinical, or biomedical datasets is preferred
Ability to work in a fast-paced, dynamic environment managing multiple priorities involving multiple entities
Intermediate to excellent proficiency in Microsoft Word, Excel, Outlook, and PowerPoint
Reliable WiFi connection
Minimum availability of 20 hours per week, Monday through Friday between 8:30am and 5pm
Must be legally authorized to work in the United States for any employer without sponsorship, now or in the future
For remote roles, work must be performed inside the United States, not in a foreign country

Benefits

Comp & perks

Ongoing professional development and training
Access to Heart U, the Association’s online university
Employee Resource Groups (ERGs)
Professional mentoring program
Teladoc General Medical and Behavioral Health programs
Employee Assistance Program (EAP) at no cost
Work-life harmonization resources and support