The Applied Artificial Intelligence Engineer is part of the Education Design and Informatics team within the Office of Health Sciences Education at Vanderbilt University School of Medicine. The Education Design & Informatics Team (EDI) is responsible for technology, instructional design, data infrastructure, and quality improvement for Vanderbilt's MD program and affiliated health professions education.
We're seeking an AI Engineer to help us realize our vision for precision medical education—using data and AI to personalize learning, predict learner needs, and improve educational outcomes at scale.
You'll be our first dedicated AI/ML role, working alongside a data engineer, full-stack developers, and instructional designers.
Near-term priorities include:
LLM-powered tools for learners and educators
Semantic search across educational content
Recommendation systems for personalized learning pathways
Integration of AI capabilities into VSTAR
Contribute to predictive modeling efforts, including:
Early identification of at-risk learners
Competency progression analytics
This is a high-ownership, foundational role. You'll shape AI strategy and implementation from the ground up.
This position is fully remote and reports directly to the Director of Education Design & Informatics.
Qualifications
A Bachelor’s degree in a related field from an accredited institution of higher education is necessary.
Requirements
5 – 7 years of experience is required.
Experience in applied machine learning, AI engineering, or a related field (3+ years) is necessary.
Strong Python skills and experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow (3+ years) is necessary.
Hands-on experience building applications with LLMs, including prompt engineering, embeddings, retrieval-augmented generation, and agents (1+ years) is necessary.
Experience developing backend services (FastAPI, Flask, or similar) and RESTful APIs (1+ years) is necessary.
Track record of deploying AI or ML features to production environments (1+ years) is necessary.
Comfort with SQL and working with data pipelines (3+ years) is necessary.
Ability to communicate technical concepts clearly to non-technical audiences (3+ years) is necessary.
Experience with Databricks and Azure cloud services (1+ years) is preferred.
Familiarity with MLOps tools and practices (MLflow, model registries, CI/CD for ML) (1+ years) is preferred.
Experience with vector databases (Pinecone, Weaviate, Chroma, or similar) (1+ years) is preferred.
Experience working with multiple LLM providers or open source LLMs and evaluating tradeoffs (1+ years) is preferred.
Background in building predictive models (classification, regression, forecasting) (1+ years) is preferred.
Experience in education, healthcare, or other mission-driven sectors (1+ years) is preferred.
Familiarity with the unique considerations of AI in educational contexts (pedagogical alignment, learner privacy, appropriate automation) (1+ years) is preferred.
Demonstrated self-direction and ownership mentality in previous roles is necessary.
Benefits
Fully remote position with potential for hybrid availability.