Intern, Data Science, Machine Learning, AI

This is a fully remote position, open to applicants in Texas.

📋 Description

• Assist in the design and creation of applications powered by LLMs and agentic AI workflows tailored for clinical, biomedical, and operational research scenarios.

• Utilize LLMs for various modeling and analytical tasks, including information extraction, classification, summarization, question answering, and orchestrating workflows.

• Engage in experimentation with prompt design, structured outputs, retrieval-augmented generation, embeddings, vector search, tool utilization, and multi-step agent workflows.

• Prepare, clean, organize, and document data utilized in LLM and generative AI experiments.

• Create reproducible prototypes and workflows using Python along with approved AI/ML tools and platforms.

• Design and execute evaluations of LLM systems employing both quantitative and qualitative metrics.

• Conduct validation, error analysis, robustness testing, and comparative assessments of model or workflow alternatives.

• Evaluate hallucination, factual consistency, relevance, reliability, bias, privacy, and reproducibility.

• Document methodologies, assumptions, prompts, evaluation outcomes, limitations, and suggested enhancements.

• Contribute to technical documentation, presentations, abstracts, manuscripts, and discussions across functional projects.

⛳️ Requirements

• Actively pursuing an MS or PhD in Computer Science, Artificial Intelligence, Biomedical Informatics, Data Science, Statistics, Engineering, Public Health, or a related quantitative discipline.

• Coursework or project experience involving LLMs, generative AI, natural language processing, retrieval-augmented generation, or AI agents.

• Familiarity with APIs or open-source frameworks for building and testing LLM applications.

• Proficient in Python programming and knowledgeable about common data analysis or machine learning libraries.

• Capable of understanding and applying foundational LLM concepts such as tokens, context windows, embeddings, prompting, retrieval, and generation.

• Strong analytical, problem-solving, organizational skills, and attention to detail.

• Dedicated to reproducible research, responsible AI practices, data integrity, and thorough documentation.

• Effective communication skills and the ability to collaborate with both technical and non-technical team members.

• Experience with cloud computing and/or high-performance computing environments, such as AWS, Snowflake, Azure, or GCP.

• Knowledge of model evaluation, experimental design, error analysis, version control, or reproducible workflow methodologies.

• Preferred experience with healthcare, clinical, or biomedical datasets.

• Ability to thrive in a fast-paced, dynamic environment while managing multiple priorities across various entities.

• Intermediate to advanced proficiency in Microsoft Word, Excel, Outlook, and PowerPoint.

• Reliable WiFi connection.

• Minimum availability of 20 hours per week, Monday through Friday between 8:30 AM and 5 PM.

• Must possess legal authorization to work in the United States for any employer without sponsorship, now or in the future.

• For remote positions, work must be conducted within the United States, not in a foreign country.

🏝️ Benefits

• Continuous professional development and training opportunities.

• Access to Heart U, the Association’s online university.

• Participation in Employee Resource Groups (ERGs).

• Professional mentoring program.

• Teladoc General Medical and Behavioral Health services.

• Complimentary Employee Assistance Program (EAP).

• Resources and support for work-life harmonization.