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.

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.

The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data.

• You are passionate about transforming raw healthcare data into valuable insights.
• You believe in the critical role of AI in advancing machine learning in healthcare.
• You thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams.
• You are excited to work with patient-level data and embrace challenges related to data diversity and complexity.

• Support complex scientific and research programs related to area of specialization; analyze data, monitor and oversee experimental process, and design and develop prototypes, specialized equipment, and/or systems.
• Collaborate with scientists, engineers, or senior administrative officers to oversee complex non-routine analyses, select optimum solutions, and perform corrective modifications to equipment and system designs.
• Carry out all activities, including troubleshooting and resolving routine problems for scientist or engineers, independently.
• Collaborate with senior engineers and scientists to design and develop special purpose equipment and/or systems.
• Participate in the planning, design, and implementation of scientific or engineering initiatives, and work toward project
• objective.
• Oversee a laboratory space or unit, and supervise the work of technicians and other staff associated with the group.
• Serve as a resource in review of research proposals and research capabilities, and make recommendations.
• Establish, communicate, and enforce compliance with health and safety policies and procedures.
• Develop training manuals and safety guidelines, and train new instrumentation users, researchers, and/or technical staff.
• Perform supervisory duties, including overseeing the work of technicians and other staff associated with the group/project, supervising the regular installation, maintenance, and operation of complex scientific or engineering projects, and training technicians, operators, and others working in particular scientific or…