Research and Development Scientist and Engineer (24-Month Fixed-Term)

Stanford University; Palo Alto (CA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Stanford University seeks a Machine Learning Engineer (Research and Development Scientist and Engineer 1) to monitor AI tools used in clinics and to help develop automated checks that ensure tools work as expected. The role involves handling health records, medical images, clinical notes, wearables, and integration with AI systems in a hybrid work setting.

Kandidat should have a Doctorate in a quantitative field and experience in Python and modern software tools, with a focus on safe AI

Qualifications

• PhD in CS/DS/biomedical fields or related quantitative discipline with research experience.

Responsibilities

• Design and develop a monitoring system for evaluating clinical AI tools.
• Coordinate the phases of building automated checks for AI tool performance.
• Collect, manage, and clean datasets related to clinical AI tools.
• Advise faculty, clinicians and research staff on monitoring methods.
• Prepare reports and documentation to enable reproducibility of work.

Skills

Data analysis

Programming

Education

Doctorate degree in Computer Science, Data Science, Bioengineering, Statistics, or related field

Tools

Python

Claude Code

Job description

Stanford University is seeking a Machine Learning Engineer (Research and Development Scientist and Engineer 1) to help monitor AI tools that are or will be used autonomously in clinics. The candidate will help build and maintain a system that keeps track of how clinical AI tools are performing over time, including noticing when the data they see differs from what they were built and tested on. The candidate will also help develop automated checks that evaluate whether these tools are working as expected. The candidate will manage and organize data such as health records, medical images, clinical notes, wearables, and how they interact with AI systems and tools. The candidate is expected to have experience with standard programming and data analysis tools (such as Python), modern software engineering tools (such as Claude Code), and an interest in the safe use of AI in healthcare.

DESIRED QUALIFICATIONS

Doctorate degree in computer science, data science, bioengineering, statistics, or other related quantitative fields. Previous research or laboratory experience preferred.

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 his or her job.

WORKING CONDITIONS

• 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.
  

ADDITIONAL WORKING CONDITIONS

This will be a hybrid position, with work occurring both remotely and in person on the Stanford campus.

ADDITIONAL DUTIES INCLUDE*

• Design and develop a monitoring system and automated checks for evaluating clinical AI tools, and coordinate the phases of this work.
• Develop methods to detect changes in the data clinical AI tools see, investigate unusual or problematic data, determine the cause, and suggest solutions.
• Create new evaluation harnesses and software tools, using modern agentic tools, to test and monitor clinical AI systems.
• Collect, manage, and clean datasets related to clinical AI tools, and advise faculty, clinicians, and research staff on monitoring and evaluation methods.
• Prepare reports, charts, graphs and tables for investigators, contribute to manuscripts and grant applications, and document data sources, evaluation procedures, and software so that others can understand and repeat them.

* - Other duties may also be assigned.