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Intern - Generative AI Developer

Cotiviti

Salary not specified
Sep 6, 2025
Remote, US
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Cotiviti is looking to research and develop advanced healthcare informatics, particularly in the realm of Generative AI and emerging Artificial General Intelligence, to support improvements in healthcare treatment, payment, and operations.

Requirements

  • 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.

Responsibilities

  • 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.
  • 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.

Other

  • Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.
  • Demonstrated interest or experience in AI, healthcare technology, or informatics research.
  • Ability to work collaboratively and communicate effectively with cross-functional teams.
  • Communicating with others to exchange information.
  • Assessing the accuracy, neatness, and thoroughness of the work assigned.