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

• This role is for one of our clients
• 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.