Stanford University School of Medicine is hiring: Science and Engineering Associ
Stanford University School of Medicine, Palo Alto, CA, United States
Overview
Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the ARPA-H/BDF grant. The grant requires 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.
Responsibilities
Build end-to-end data pipelines and infrastructure for ML models used in the grant.
Develop robust and modular software engineering infrastructures for training and inference of ML models for various downstream applications.
Make recommendations and design decisions for languages, tools, and platforms used in software and data projects.
Collaborate with scientists, engineers, and senior staff to oversee analyses, design and develop prototypes, and improve equipment or systems as needed.
Troubleshoot and resolve problems for scientists or engineers; work independently on complex data challenges when appropriate.
Participate in planning, design, and implementation of scientific or engineering initiatives toward project objectives.
Oversee laboratory space or unit and supervise technicians and other staff.
Review research proposals and capabilities; provide recommendations and ensure health and safety compliance.
Develop training manuals and safety guidelines; train new instrumentation users and technical staff.
Perform supervisory duties including overseeing work of technicians and ensuring installation, maintenance, and operation of complex projects.
Other duties may be assigned as needed.
Qualifications
Ability to install, configure, and implement machine learning algorithms in platforms such as PyTorch and JAX and inference platforms such as Hugging Face, Gradio, and Streamlit.
Experience with cloud infrastructure and CI/CD.
Experience with machine learning operations (MLOps) processes and working with healthcare data.
Experience building software and data infrastructure for analytics, including Python and BigQuery SQL for processing large datasets.
Experience researching and prototyping state-of-the-art foundation models for multi-modal data (radiology, EMR, pathology).
Ability to design evaluation frameworks, benchmark datasets, and report metrics.
Experience with shared code environments (e.g., GitHub) and collaboration with developers; responsiveness to issues and pull requests.
Experience in leading code reviews and applying design principles and best practices.
Experience working in a HIPAA-regulated environment.
Publications in AI for medical applications are a plus.
Education & Experience (required)
Bachelor’s degree in engineering, science, or related field and three years of relevant experience; or a combination of education and relevant experience.
Knowledge, Skills And Abilities (required)
Demonstrated knowledge of advanced scientific or engineering principles and practices.
Experience applying complex scientific and engineering principles and performing technical services involving development and performance.
Proficiency with relevant software applications and ability to oversee instrumentation or system installation.
Ability to collaborate with senior staff to design and develop systems.
Experience overseeing major scientific or engineering initiatives and ensuring project objectives are met.
Ability to review research proposals, evaluate capabilities, and make recommendations.
Ability to enforce health and safety policies and supervise a laboratory space or unit.
Certifications & Licenses
None
Pay and Benefits
Expected pay range: $122,929 to $145,389 per annum. Stanford provides information on salaries and benefits; specifics discussed during hiring.
Benefits information: The Cardinal at Work website provides details on benefits and rewards.
Specifics about the rewards package for this position may be discussed during the hiring process.
EEO and Accommodations
Consistent with applicable law, the University provides reasonable accommodations to applicants and employees with disabilities. For accommodations, contact Stanford University Human Resources. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.
Desired Qualifications
Proficiency with containerization tools (e.g., Docker).
Familiarity with healthcare data standards and regulatory requirements.
Education & Experience (preferred)
Not specified beyond above.
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Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the ARPA-H/BDF grant. The grant requires 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.
Responsibilities
Build end-to-end data pipelines and infrastructure for ML models used in the grant.
Develop robust and modular software engineering infrastructures for training and inference of ML models for various downstream applications.
Make recommendations and design decisions for languages, tools, and platforms used in software and data projects.
Collaborate with scientists, engineers, and senior staff to oversee analyses, design and develop prototypes, and improve equipment or systems as needed.
Troubleshoot and resolve problems for scientists or engineers; work independently on complex data challenges when appropriate.
Participate in planning, design, and implementation of scientific or engineering initiatives toward project objectives.
Oversee laboratory space or unit and supervise technicians and other staff.
Review research proposals and capabilities; provide recommendations and ensure health and safety compliance.
Develop training manuals and safety guidelines; train new instrumentation users and technical staff.
Perform supervisory duties including overseeing work of technicians and ensuring installation, maintenance, and operation of complex projects.
Other duties may be assigned as needed.
Qualifications
Ability to install, configure, and implement machine learning algorithms in platforms such as PyTorch and JAX and inference platforms such as Hugging Face, Gradio, and Streamlit.
Experience with cloud infrastructure and CI/CD.
Experience with machine learning operations (MLOps) processes and working with healthcare data.
Experience building software and data infrastructure for analytics, including Python and BigQuery SQL for processing large datasets.
Experience researching and prototyping state-of-the-art foundation models for multi-modal data (radiology, EMR, pathology).
Ability to design evaluation frameworks, benchmark datasets, and report metrics.
Experience with shared code environments (e.g., GitHub) and collaboration with developers; responsiveness to issues and pull requests.
Experience in leading code reviews and applying design principles and best practices.
Experience working in a HIPAA-regulated environment.
Publications in AI for medical applications are a plus.
Education & Experience (required)
Bachelor’s degree in engineering, science, or related field and three years of relevant experience; or a combination of education and relevant experience.
Knowledge, Skills And Abilities (required)
Demonstrated knowledge of advanced scientific or engineering principles and practices.
Experience applying complex scientific and engineering principles and performing technical services involving development and performance.
Proficiency with relevant software applications and ability to oversee instrumentation or system installation.
Ability to collaborate with senior staff to design and develop systems.
Experience overseeing major scientific or engineering initiatives and ensuring project objectives are met.
Ability to review research proposals, evaluate capabilities, and make recommendations.
Ability to enforce health and safety policies and supervise a laboratory space or unit.
Certifications & Licenses
None
Pay and Benefits
Expected pay range: $122,929 to $145,389 per annum. Stanford provides information on salaries and benefits; specifics discussed during hiring.
Benefits information: The Cardinal at Work website provides details on benefits and rewards.
Specifics about the rewards package for this position may be discussed during the hiring process.
EEO and Accommodations
Consistent with applicable law, the University provides reasonable accommodations to applicants and employees with disabilities. For accommodations, contact Stanford University Human Resources. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.
Desired Qualifications
Proficiency with containerization tools (e.g., Docker).
Familiarity with healthcare data standards and regulatory requirements.
Education & Experience (preferred)
Not specified beyond above.
#J-18808-Ljbffr