ML Engineer – Healthcare Data Curation & Model Workflows

About the role

The Department of Biomedical Data Science at Stanford University seeks a Machine Learning Engineer to support complex scientific and research programs related to AI and ML tools for biomedical applications. The role involves building end-to-end data pipelines and infrastructure for ML models, designing and developing special purpose equipment and systems, and collaborating with multidisciplinary teams.

Responsibilities

• 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 objectives
• 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 engineering function area

Requirements

• Ability to install, configure, and implement machine learning algorithms in modern training platforms (such as PyTorch, JAX) and inference platforms (such as Hugging Face, gradio, streamlit)
• Experience with cloud infrastructure and CI/CD
• Experience overseeing, developing or implementing machine learning operations (MLOps) processes
• Experience working with healthcare data
• Experience in building software and data infrastructure for analytics team, including ability to write Python and BigQuery SQL for processing large datasets
• Research and prototype state-of-the-art foundation models for multi-modal data including radiology, EMR and pathology
• Design algorithm evaluation frameworks, benchmark datasets and report metrics
• Experience in shared code environments such as GitHub and collaborate with other developers and be responsive to GitHub issues and pull requests
• Lead code reviews for projects/systems as an independent reviewer applying design principles, coding standards and best practices
• Experience working in a HIPAA regulated environment
• Experience with publications in AI for medical applications in healthcare journals or ML conferences a plus

Qualifications

• Bachelor’s degree in engineering, science, or related field and three years of relevant experience; or a combination of education and relevant experience
• Demonstrated knowledge and skills of advanced scientific or engineering principles and practices
• In-depth experience with software applications, systems, or programs relevant for the job
• Ability to independently oversee and manage instrumentation or system installation
• Ability to collaborate with senior engineering and scientific staff to design and develop special purpose equipment and/or systems
• Experience overseeing the plan, design, and implementation of major scientific or engineering initiatives and ensuring project objective are met
• Demonstrated ability to review research proposals, evaluate research capabilities, and make recommendations
• Demonstrated ability to establish, communicate, and enforce compliance with health and safety policies and procedures
• Experience overseeing a laboratory space or unit and supervising the work of technicians and other staff associated with the group
• Demonstrated ability to effectively supervise and train a diverse work staff