Remote | Member of Technical Staff, Medical Research — $400,000–$800,000/year
About The Position
This full-time, fully remote role is for an experienced medical or healthcare researcher contributing to research on trustworthy healthcare-focused AI systems. The work includes designing rigorous evaluation frameworks, developing benchmark datasets and validation environments, analyzing medical reasoning and failure patterns, and collaborating with clinicians, researchers, and engineers to improve AI systems used in healthcare, biomedical, and clinical workflows. The role covers healthcare AI evaluation, medical research, benchmark development, evidence synthesis, and reliability analysis. Assignments may span clinical reasoning, healthcare decision support, biomedical research, healthcare analytics, and agentic medical workflows. Strong research-design, evidence-evaluation, and healthcare-domain expertise are central. Research priorities, project scope, benchmarks, and evaluation standards may evolve over time. Work must be completed without using confidential, proprietary, patient-identifiable, or unpublished information belonging to any employer, healthcare organization, research institution, client, or other third party. This opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
Requirements
- Advanced degree in Medicine, Public Health, Nursing, Pharmacy, Biomedical Sciences, Epidemiology, Health Economics, or a related healthcare field; examples include MD, DO, PhD, MPH, PharmD, or equivalent advanced qualifications.
- Deep expertise in clinical practice, healthcare operations, biomedical research, public health, healthcare analytics, or evidence-based medicine.
- Demonstrated experience conducting medical, clinical, biomedical, or healthcare research.
- Strong understanding of research design and evidence evaluation.
- Strong knowledge of healthcare decision-making processes.
- Excellent analytical reasoning and scientific communication skills.
- Experience working across multidisciplinary research, healthcare, technology, or policy environments.
- Strong research-design, evidence-evaluation, and healthcare-domain expertise.
- Ability to complete work without using confidential, proprietary, patient-identifiable, or unpublished third-party information.
Nice To Haves
- Familiarity with digital health or clinical decision-support systems.
- Experience with healthcare analytics or health technology assessment.
- Knowledge of healthcare quality measurement, clinical guidelines, evidence synthesis, or benchmarking.
- Published medical, clinical, healthcare, or biomedical research.
- Experience with clinical studies, systematic reviews, or healthcare evaluation initiatives.
- Experience with AI evaluation or benchmarking; useful but not required.
Responsibilities
- Design evaluation frameworks for AI systems operating in medical and healthcare domains.
- Develop benchmark structures, scoring methodologies, and clinical quality rubrics.
- Define validation protocols and consistent standards for measuring medical reasoning and decision-support quality; refine criteria as model capabilities and use cases evolve.
- Conduct applied research on medical reasoning and evidence-based decision-making, including analysis of clinical workflows and healthcare information-synthesis processes.
- Evaluate the quality and relevance of medical and biomedical evidence and translate complex findings into structured research conclusions.
- Develop benchmark datasets based on realistic healthcare and biomedical scenarios and create evaluation environments reflecting practical clinical and research workflows.
- Design tasks testing reasoning, evidence integration, and healthcare decision support; support agentic medical and healthcare evaluation workflows.
- Analyze model performance, identify reasoning weaknesses and failure patterns, assess safety and reliability, investigate divergence from professional standards, and recommend improvements to model quality and trustworthiness.
- Collaborate with clinicians, researchers, engineers, and multidisciplinary stakeholders.
- Produce research reports, evaluation methodologies, and best-practice guidelines; contribute to healthcare AI benchmarking and reliability standards.
- Monitor developments in medicine, healthcare delivery, biomedical research, and AI, and help shape practices for evaluating healthcare-focused AI systems.
Benefits
- Equity compensation and performance-based incentives may be available depending on role and applicable policies.
- Benefits may include health-insurance support, paid time off, retirement-plan contributions, and other employment benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
