The AI Engineer bridges the gap between data science and implementation, supporting the development, deployment, and maintenance of production-grade applications that leverage Machine Learning (ML) and Artificial Intelligence (AI)
Job Summary
The AI Engineer bridges the gap between data science and implementation, supporting the development, deployment, and maintenance of production-grade applications that leverage Machine Learning (ML) and Artificial Intelligence (AI).
They partner with clinicians, subject matter experts, analytics developers, researchers, and data engineers to ensure delivered solutions provide actionable real-time insights aligned with clinical, financial, and operational goals.
Children’s is committed to putting you first, with a company culture of People first. Children always.
Matching Summary
The AI Engineer bridges the gap between data science and implementation, supporting the development, deployment, and maintenance of production-grade applications that leverage Machine Learning (ML) and Artificial Intelligence (AI).
Skills & Requirements
Must-have
Machine Learning Engineering experience
production environment implementation
Python, SQL, PySpark, Scala
software development methodologies
Git source control
Azure, AWS, Google Cloud
Nice-to-have
healthcare data experience
Epic certification
Azure certifications
foundation large language models
agile, iterative frameworks
Key Requirements
2 years ML Engineering, Data Science, or Data Engineering