Applied Artificial Intelligence Engineer
Vanderbilt University Medical Center
full-time
Posted on:
Location Type: Remote
Location: Tennessee • United States
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About the role
- Design and build AI-powered features for VSTAR and other EDI platforms, including intelligent tutoring capabilities, semantic search, content recommendations, and LLM-based tools for learners and educators
- Apply appropriate AI implementation patterns and strategies such as RAG architectures, agentic workflows, prompt engineering strategies, and LLM orchestration patterns appropriate to educational use cases
- Develop backend services and APIs that expose AI capabilities for integration into VSTAR and other applications, working with the development team to determine appropriate integration patterns
- Evaluate vender versus open-source AI products and services based on performance, cost, and reliability considerations
- Ensure responsible AI practices, including appropriate guardrails, content filtering, and transparency in AI-assisted features
- Build and maintain ML pipelines in Databricks for feature engineering, model training, and evaluation
- Deploy models and AI services to production with appropriate monitoring, logging, and error handling
- Implement MLOps practices proportionate to our maturity: version control, testing, documentation, and reproducibility
- Ensure performance, reliability, and scalability of AI-powered services
- Own the full lifecycle of deployed AI features, including maintenance, iteration, and retirement
- Partner with data engineering to ensure AI systems integrate cleanly with our data infrastructure
- Collaborate with software developers to integrate AI features into existing applications
- Proactively communicate progress, challenges, and decisions to the team through regular check-ins, documentation, and asynchronous updates
- Work with product and educational leadership to identify high-impact AI opportunities
- Contribute to EDI's AI strategy and help establish best practices for responsible AI development in medical education
- Maintain clear documentation and support knowledge sharing across the team
- Stay current with developments in AI tooling, particularly as they apply to education and knowledge work
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
- Health insurance
- Professional development opportunities
- Flexible work arrangements
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Pythonmachine learningAI engineeringML frameworksscikit-learnPyTorchTensorFlowbackend servicesRESTful APIsSQL
Soft Skills
communicationself-directionownership mentality