Clinical Medicine Domain Expert

Weekday AI (YC W21); California City (CA); Hybrid; USD 96,000 - 152,000; Full time

Job summary

Weekday AI is seeking a Clinical Medicine Domain Expert to shape AI-driven clinical reasoning benchmarks. This full-time, 40-hour-per-week role is based in the Bay Area, with hybrid on-site collaboration.

You will evaluate AI outputs, define reference solutions, and craft rigorous clinical tasks spanning internal medicine, oncology, radiology, and more. The ideal candidate is an experienced clinician with MD/DO, US licensure, board certification, and a track record of clinical leadership.

Qualifications

• MD/DO from an accredited medical school with residency completion.
• Active and unrestricted medical license in at least one U.S. state.
• Board certification in the candidate's primary medical specialty.

Responsibilities

• Review and assess clinical knowledge tasks and AI outputs for accuracy, safety, and relevance.
• Identify missing reasoning steps, unsafe recommendations, and deviations from guidelines.
• Develop clear instruction specifications and high-quality reference solutions.

Skills

Clinical decision making

AI evaluation

Data quality

Benchmark design

Clinical feedback

Cross-functional collaboration

Education

MD/DO with residency

Medical licensure in US

Board Certification in primary specialty

Tools

AI tools

Research software

Job description

Compensation: $70 - $110 per hour

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.

Requirements

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.