About the Role
Physician Annotator supporting clinical AI development in nuclear medicine through data annotation, model evaluation, and clinical guidance
Responsibilities
- Contribute clinical expertise to develop and refine annotation protocols and clinical guidelines for various use cases
- Identify edge cases, ambiguities, and potential biases in clinical data and AI model behavior
- Engage in applied clinical AI research, including forming hypotheses and assessing model performance
- Help generate research insights that may support internal studies, publications, or regulatory submissions
- Review nuclear medicine imaging studies and provide clinical annotations to train and refine AI models
- Analyze studies both with and without AI assistance to accurately identify and outline regions of interest across diverse imaging types such as FDG, PSMA-PET/CT, and SPECT
- Verify AI-generated outputs for clinical accuracy, safety, and relevance across specified use cases
- Examine model errors and edge cases and deliver structured clinical feedback to enhance model performance
- Guide the selection of clinically relevant metrics, thresholds, and evaluation criteria
- Deliver clear, actionable clinical feedback on product features and user workflows
- Advise product teams on prioritizing features based on clinical impact, risk, and feasibility
- Support retrospective and prospective analyses to evaluate the clinical validity and practical utility of AI models
- Assess the usability and integration of AI tools within clinical workflows from a physician's perspective
- Collaborate asynchronously with clinical, product, and data science teams
- Serve as a part-time clinical advisor to enable rapid iteration and informed decision-making
Requirements
- MD or DO degree with active or eligible medical licensure
- Specialty training or board certification in nuclear medicine
- Experience interpreting a variety of nuclear medicine imaging modalities including PET/CT and SPECT
- Strong understanding of radiopharmaceuticals and their clinical applications
- Proven ability to interpret imaging with precision and clinical context
- Familiarity with clinical workflows in diagnostic imaging environments
- Demonstrated attention to detail and consistency in documentation and annotation
- Ability to identify subtle imaging findings and provide accurate clinical interpretations
- Experience with digital imaging platforms such as PACS or DICOM viewers
- Strong communication skills for conveying clinical insights to technical teams
Nice to Have
- Active clinical practice in nuclear medicine or related radiology subspecialty
- Experience with AI or machine learning applications in medical imaging
- Prior involvement in clinical research or data annotation projects
- Familiarity with regulatory requirements for AI-based medical devices
- Exposure to model validation or performance evaluation in clinical settings
- Experience working in cross-functional or interdisciplinary teams
- Background in medical education or protocol development
Tech Stack
AI/ML model interfaces for medical imaging, DICOM and PACS integration tools, Cloud-based annotation platforms, Version control systems (e.g., Git), Data privacy and compliance frameworks (e.g., HIPAA-compliant environments)
Benefits
- Flexible part-time schedule compatible with clinical practice
- Opportunity to contribute to cutting-edge clinical AI development
- Remote work arrangement with asynchronous collaboration
- Compensation commensurate with experience and expertise
- Involvement in research and potential for co-authorship on publications
