Board-Certified Physician (MD / DO, Any Specialty), Clinical AI Expert

Compensation: $70 - $110 per hour

Location: Bay Area, California, United States Work Arrangement: Hybrid (On-site multiple days per week, as required) Employment Type: Full-Time, W-2 Work Commitment: 40 hours per week Initial Engagement: 6 months

Job Overview

We are seeking an experienced, board-certified physician to work directly with the research and program management teams at a leading AI lab, helping advance how next-generation AI models understand, reason about, and respond to real-world clinical challenges.

As a Clinical AI Expert, you will bring your medical expertise and independent clinical judgment to evaluate AI-generated medical content, develop high-quality clinical benchmarks, and establish reference solutions that define what accurate, safe, and evidence-based medical reasoning looks like.

This role is designed for practicing physicians with substantial post-residency experience, strong specialization in a clinical discipline, and the ability to assess medical reasoning beyond surface-level correctness. You will collaborate closely with AI researchers and engineering teams to improve the quality, reliability, and clinical relevance of advanced AI systems.

This is a full-time W-2 employment opportunity with a hybrid work arrangement in the San Francisco Bay Area. You will receive client-issued accounts and equipment and work directly within the client's internal tools and research environment.

Key Responsibilities

• Clinical Quality Assurance: Review and evaluate clinical knowledge tasks and AI-generated medical responses, identifying gaps in clinical reasoning, missing considerations, unsafe recommendations, and deviations from established medical guidelines.
• Instruction Specifications and Reference Solutions: Develop detailed task specifications, create accurate reference answers, and design clinical problems that reflect real-world medical practice and decision-making.
• Clinical Benchmark Development: Design challenging, specialty-specific clinical tasks and evaluation datasets to measure the accuracy, depth, safety, and reliability of AI-generated medical reasoning.
• Medical Content Evaluation: Assess AI responses across diagnosis, treatment planning, patient management, clinical guidelines, and specialty-specific medical scenarios.
• Technical Feedback: Provide clear, structured, and actionable written feedback to help research teams identify weaknesses and improve model performance.
• Research Collaboration: Work with AI researchers, engineers, and specialists from adjacent domains to establish consistent evaluation standards and translate clinical expertise into measurable assessment criteria.
• Clinical Standards: Help develop medicine-specific evaluation frameworks, tools, and workflows that ensure AI outputs meet professional clinical standards.

Required Qualifications

• MD or DO degree from an accredited medical school.
• Completed residency training in a recognized medical specialty.
• Minimum of 4 years of independent clinical practice following residency. Residency and fellowship training do not count toward this requirement.
• Active, unrestricted medical license in at least one US state.
• Current board certification in the candidate's respective specialty.
• Demonstrated expertise in a defined clinical specialty, including but not limited to:
• Internal Medicine
• Oncology
• Radiology
• Emergency Medicine
• General or Specialty Surgery
• Psychiatry
• Cardiology
• Neurology
• Pediatrics
• Other recognized medical specialties and subspecialties
• Clear professional progression into senior clinical responsibilities, such as Attending Physician, Medical Director, Division Chief, Associate Professor, Professor, or Chief Medical Officer.
• Proven ownership of clinical decisions and experience applying independent medical judgment in patient care.
• Practical experience using large language models (LLMs) in a professional setting, with the ability to distinguish clinically sound reasoning from plausible but medically incorrect responses.
• Excellent written communication skills and the ability to explain complex clinical concepts through precise, well-structured feedback.
• Ability to commit reliably to 40 hours per week for the initial six-month engagement.

Preferred Qualifications

• Experience in utilization management, clinical informatics, medical affairs, or clinical quality assurance.
• Experience developing clinical guidelines, medical protocols, or evidence-based evaluation frameworks.
• Previous involvement in medical research, clinical education, or multidisciplinary healthcare initiatives.
• Familiarity with AI model evaluation, clinical benchmark development, or medical dataset quality assessment.

Employment Details

• Work Location: San Francisco Bay Area, California, United States.
• Work Arrangement: Hybrid, requiring on-site collaboration with the client's team multiple days per week, as needed.
• Employment Type: Full-time, W-2 employment.
• Work Schedule: 40 hours per week.
• Initial Duration: 6 months.
• Equipment and Access: Client-issued accounts and equipment will be provided.
• Work Environment: Direct collaboration with the client's research and program management teams, using internal tools and established workflows.
• Engagement Structure: This is a structured, role-based employment opportunity rather than a freelance or project-based engagement.

Location and Relocation Requirements

• Candidates must currently reside in the San Francisco Bay Area or be willing to relocate before the engagement begins.
• Relocation expenses must be covered by the candidate.
• Relocation assistance is not provided.
• Candidates must be available for regular on-site collaboration with the client's team multiple days each week, as required.
• This is not a fully remote position.