Intern, Agentic AI Research

Role Overview

• Demonstrates a strong understanding of technology trends, research, and emerging technologies relevant to the healthcare industry, particularly in Generative AI.
• Assists in developing and improving LLMs and ML tools used across the organization.
• Assists in establishing and maintaining an Artificial Intelligence Governance Program.
• Gain hands-on experience in generative AI model development, architecture design, and database management.
• Conduct research on Agentic AI models and their potential impact on healthcare workflows and decision-making.
• Assist in designing, developing, and testing autonomous AI agents and generative AI systems tailored for healthcare informatics.
• Support efforts to establish and maintain an Artificial Intelligence Governance Program with a focus on agentic AI ethics and safety.
• Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.
• Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.
• Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.
• Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.
• Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.
• Supports vendor evaluations and contributes to collaborations with vendors.
• Assists as a liaison between academic institutions, professional organizations, and research groups as needed.

Requirements

• Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science, AI, etc.) with preference of a PhD.
• Demonstrated interest or experience in AI, healthcare technology, or informatics research.
• Strong foundational knowledge in generative AI model development, architectures, and vector databases.
• Hands-on experience with working with Machine Learning and Deep Learning models.
• Experience with LLM/RAG models and LLM fine-tuning is a plus.
• Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions.
• Experience with vector embeddings and databases is a plus.
• Ability to work collaboratively and communicate effectively with cross-functional teams.

Tech Stack

• AWS
• Azure
• Cloud

Benefits

• Must be able to provide a dedicated, secure work area.
• Must be able to provide high-speed internet access/connectivity and office setup and maintenance.