Clinical Medicine Domain Expert

Weekday AI; California City (CA); Hybride; USD 96 000 - 152 000; Plein temps

Résumé du poste

Weekday AI is seeking an experienced Clinical Medicine Domain Expert to help shape its GenAI evaluation framework. You will review AI outputs, develop reference solutions, and create challenging clinical benchmarks.

Remote work is not available; the Bay Area location requires on-site collaboration several days weekly. We require an MD/DO with 4+ years post-residency experience, active US licensure, and board certification.

Qualifications

• MD or DO from an accredited medical school with residency
• Minimum 4 years of post-residency clinical practice
• Active and unrestricted medical license in at least one US state
• Board certification in the primary medical specialty
• Deep expertise in a defined clinical specialty (e.g., Internal Medicine, Oncology, Radiology, Emergency Medicine, Surgery, Psychiatry or subspecialties)
• Experience with AI/tools in professional setting to assess clinically sound reasoning

Responsabilités

• Review clinical knowledge tasks and AI outputs for accuracy, safety, and relevance
• Develop instruction specifications and reference solutions for complex clinical problems
• Create clinical tasks representing real-world medical problems for evaluation benchmarks
• Collaborate with researchers and clinicians to maintain evaluation standards
• Provide precise written feedback to improve AI system quality

Connaissances

AI fluency

Clinical judgment

Written communication

40 hours/week

Formation

MD/DO from accredited medical school

Residency completed

Board certification

Medical licensure (US)

Description du poste

This role is for one of our clients

Compensation: $70 - $110 per hour

We are seeking an experienced Clinical Medicine Domain Expert to contribute to a cutting-edge GenAI initiative focused on improving how advanced AI models understand, reason about, and respond to real-world clinical scenarios.

Your clinical expertise will be central to this role. You will evaluate medical knowledge tasks and AI-generated outputs, develop detailed instructions and reference solutions, and create rigorous benchmarks that establish what high-quality clinical reasoning looks like. We are looking for an experienced practicing clinician with deep expertise in a defined medical specialty.

This is a full-time position requiring 40 hours per week for an initial six-month engagement. The role involves working closely with research and program teams and using standard enterprise tools and workflows.

Location: Hybrid role based in the Bay Area, California. Candidates must be based in the Bay Area and able to work on-site with the team multiple days per week when required. This is not a fully remote position. Candidates currently outside the Bay Area must be willing to relocate at their own expense before the engagement begins. Relocation assistance is not provided.

Key Responsibilities

Clinical Data Quality & Evaluation

• Review and assess clinical knowledge tasks and AI-generated medical outputs for accuracy, safety, completeness, and clinical relevance.
• Identify missing reasoning steps, unsupported conclusions, unsafe recommendations, deviations from established guidelines, and clinically inappropriate responses.
• Evaluate whether AI-generated answers meet the standards expected in real-world clinical practice.

Instruction & Reference Dataset Development

• Develop clear, detailed instruction specifications that define expected clinical reasoning and outcomes.
• Create high-quality reference solutions for complex clinical problems and scenarios.
• Develop new clinical tasks that accurately represent how healthcare professionals evaluate and solve real-world medical problems.

Benchmark & Evaluation Development

• Design challenging clinical scenarios and evaluation datasets that test medical reasoning, decision-making, and domain knowledge.
• Contribute to the development of medicine-specific benchmarks, tools, and evaluation methodologies.
• Help establish measurable standards for assessing the quality and reliability of AI-generated clinical responses.

Expert Calibration & Collaboration

• Collaborate with researchers and specialists from adjacent medical and technical disciplines to maintain consistent evaluation standards.
• Translate practical clinical judgment and experience into explicit, structured, and teachable evaluation criteria.
• Provide precise written feedback that helps improve the quality and reliability of AI systems.

Core Qualifications

• Education: MD or DO from an accredited medical school, along with completion of residency training in a recognized medical specialty.
• Clinical Experience: Minimum 4 years of post-residency clinical practice. Residency and fellowship training alone do not count toward this requirement.
• Licensure: Active and unrestricted medical license in at least one U.S. state.
• Board Certification: Board certification in the candidate's primary medical specialty.
• Clinical Specialization: Deep expertise in a defined clinical specialty, such as:
  • Internal Medicine
  • Oncology
  • Radiology
  • Emergency Medicine
  • Surgery
  • Psychiatry
  • Medical subspecialties
• Experience in utilization management, clinical informatics, medical affairs, or related areas is a plus.
• Professional Seniority: Demonstrated progression into a senior clinical role such as Attending Physician, Medical Director, Division Chief, Associate Professor, Full Professor, or Chief Medical Officer.
• Proven ownership of meaningful clinical decisions, patient-care processes, clinical programs, or medical initiatives.
• AI Fluency: Practical experience using large language models or AI tools in a professional setting, with the ability to distinguish clinically sound reasoning from plausible but incorrect or unsafe outputs.
• Availability: Ability to commit reliably to 40 hours per week for an initial six-month engagement.
• Location: Must reside in or be willing to relocate to the Bay Area, California, and work on-site multiple days per week when required. Relocation expenses are not covered.
• Excellent written communication skills with the ability to provide precise, structured, and actionable clinical feedback.

Preferred Qualifications

• Experience contributing to clinical research, medical education, healthcare technology, or evidence-based clinical initiatives.
• Familiarity with clinical guidelines, medical literature, evidence-based medicine, and healthcare decision-making frameworks.
• Experience evaluating medical content, clinical documentation, or healthcare-related AI systems.
• Background working across multidisciplinary clinical and technical teams.
• Strong interest in the application of AI to healthcare and clinical decision support.

What You’ll Contribute

You will help translate real-world clinical expertise into structured evaluation frameworks, high-quality clinical tasks, reference solutions, and benchmarks for next-generation AI systems.

Your judgment will help ensure that AI models produce responses that are not only convincing and well-written, but also clinically accurate, evidence-based, safe, and aligned with professional standards of care.

Equal Opportunity

We are committed to providing equal employment opportunities to all qualified candidates. Employment decisions are made without regard to legally protected characteristics. Reasonable accommodations are available for qualified individuals throughout the application and hiring process.