Medical Expert, Part-Time

mpathic

1d•$30 - $200•Remote

About The Position

mpathic is seeking part-time Medical Experts to support confidential initiatives focused on AI safety, health information quality, and medical risk mitigation for large language models (LLMs). This role is ideal for clinicians and medical professionals who care deeply about patient safety, health equity, and the responsible use of AI in healthcare contexts. Multilingual proficiency is critical for this role. We are especially interested in experts who can work fluently across multiple languages and cultural contexts.

Requirements

Graduate-level training (past or current) in medicine, nursing, public health, or a related clinical field
Clinical experience evaluating or managing medical conditions (acute, chronic, or complex)
Strong understanding of medical ethics, patient safety, and risk communication
Fluency in English and at least one additional language
Familiarity with AI tools, LLMs, or clinical decision-support technologies
Ability to work remotely using Slack, LLM tools, and Google Docs
Comfort with ambiguity, evolving guidelines, and feedback-driven work
Willingness to sign NDAs and work with sensitive or high-risk content
Availability up to 10 hours per week and for occasional scheduled meetings

Nice To Haves

Completed degree and active licensure
5+ years of clinical or applied medical experience
Experience in emergency medicine, primary care, specialty care, or public health
Experience working with a broad range of cultures
Background in health communication, medical education, or patient-facing content
Trust & safety, content moderation, or medical data labeling experience
Interest in AI, NLP, or ML applications in healthcare
Experience reviewing or developing clinical guidelines or protocols
Membership in online communities (e.g., Discord, Reddit, professional forums)
Experience working across cultures or healthcare systems internationally

Responsibilities

Roleplaying medical and health-related scenarios with AI agents
Evaluating the medical accuracy, clarity, and safety of AI-generated health information
Red teaming for medical edge cases, unsafe guidance, and model failure modes
Identifying signs of patient distress, medical risk, or urgency escalation
Rating and evaluating AI model responses for safety, appropriateness, and harm prevention
Developing and refining medical rubrics, behavioral taxonomies, and evaluation frameworks
Conducting qualitative analysis of AI conversations involving health topics
Providing expert feedback on internal medical safety and health policy
Collaborating with engineers, researchers, and clinicians on safety metrics
Documenting edge cases, near-misses, and failure patterns
Maintaining strict confidentiality, QA standards, and ethical guidelines
Participating in interdisciplinary review and calibration sessions