Science and Engineering Associate 2 Job at Inside Higher Ed in Palo Alto
Inside Higher Ed, Palo Alto, CA, United States
Machine Learning Engineer – Stanford University
Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the DARPA/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.
About Us
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 will find this position a good fit if
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.
Duties Include
Support complex scientific and research programs related to the area of specialization; analyze data, monitor and oversee experimental processes, 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 scientists or engineers, independently.
Collaborate with senior engineers and scientists to design and develop specialty 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 areas.
Other duties may also be assigned.
Desired Qualifications
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 building software and data infrastructure for analytics teams, including ability to write Python and BigQuery SQL for processing large datasets.
Experience researching and prototyping state‑of‑the‑art foundation models for multimodal data including radiology, EMR, and pathology.
Design algorithm evaluation frameworks, benchmark datasets, and report metrics.
Experience in shared code environments such as GitHub and collaborating with other developers, 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).
Preferred Qualifications
Proficiency with containerization tools (e.g., Docker).
Familiarity with healthcare data standards and regulatory requirements.
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 and skills of advanced scientific or engineering principles and practices.
Demonstrated experience applying complex scientific and engineering principles and performing special technical services involving both development and performance.
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 objectives 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 workforce.
Certifications & Licenses
None
Physical Requirements*
Frequently grasp lightly/fine manipulation, perform desk‑based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.
Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.
Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds.
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of their job.
Working Conditions
May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80 dB TWA, allergens/biohazards/chemicals/asbestos, confined spaces, working at heights ≥10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.
May require travel.
Additional Information
Schedule: Full‑time
Job Code: 4992
Employee Status: Regular
Grade: J
Requisition ID: 108637
Work Arrangement: Hybrid Eligible
Equity & Inclusion Statement
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission.
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Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the DARPA/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.
About Us
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 will find this position a good fit if
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.
Duties Include
Support complex scientific and research programs related to the area of specialization; analyze data, monitor and oversee experimental processes, 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 scientists or engineers, independently.
Collaborate with senior engineers and scientists to design and develop specialty 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 areas.
Other duties may also be assigned.
Desired Qualifications
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 building software and data infrastructure for analytics teams, including ability to write Python and BigQuery SQL for processing large datasets.
Experience researching and prototyping state‑of‑the‑art foundation models for multimodal data including radiology, EMR, and pathology.
Design algorithm evaluation frameworks, benchmark datasets, and report metrics.
Experience in shared code environments such as GitHub and collaborating with other developers, 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).
Preferred Qualifications
Proficiency with containerization tools (e.g., Docker).
Familiarity with healthcare data standards and regulatory requirements.
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 and skills of advanced scientific or engineering principles and practices.
Demonstrated experience applying complex scientific and engineering principles and performing special technical services involving both development and performance.
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 objectives 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 workforce.
Certifications & Licenses
None
Physical Requirements*
Frequently grasp lightly/fine manipulation, perform desk‑based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.
Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.
Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds.
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of their job.
Working Conditions
May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80 dB TWA, allergens/biohazards/chemicals/asbestos, confined spaces, working at heights ≥10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.
May require travel.
Additional Information
Schedule: Full‑time
Job Code: 4992
Employee Status: Regular
Grade: J
Requisition ID: 108637
Work Arrangement: Hybrid Eligible
Equity & Inclusion Statement
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission.
#J-18808-Ljbffr