ML Engineer – Healthcare Data Curation & Model Workflows

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 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.

include:

• 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 engineering function area.
• Other duties may also be assigned

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities.

Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility.

Employees may also perform other duties as assigned.

The expected pay range for this position is $122,929 to $145,389 per annum.

Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire.

The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package.

The Cardinal at Work website ( https://cardinalatwork.stanford.edu/benefits-rewards ) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees.

Specifics about the rewards package for this position may be discussed during the hiring process.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities.

Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at stanfordelr@stanford.edu.

For all other inquiries, please submit a contact form.

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.

• 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.

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

• Proficiency with containerization tools (e.g., Docker).
• Familiarity with healthcare data standards and regulatory requirements.

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.
• 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 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.

• 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 his or her job.

• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB 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.