ML Engineer – Healthcare Data Curation & Model Workflows

**Job Description**

Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the ARPA-H/BDF grant. The grant required use of AI and ML tools for modeling and building biomedical applications that will be evaluated by clinicians. The aim is to understand the performance, safety, effectiveness, reliability, and transparency of ML/AI models intended for real-world deployment.


Reporting to the technical manager of the grant, and with guidance and dotted line reporting to senior faculty leaders, the individual will build end-to-end data pipelines and infrastructure for ML models used in the grant. They will build robust and modular software engineering infrastructures for training and inference of ML models that can be used for a variety of downstream applications and will use their knowledge to make recommendations and design decisions for languages, tools, and platforms used in software and data projects.


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