Medical Expert (Contract)

Location: United States (Remote)

Company

hirify.global develops AI-enhanced solutions and provides human services for clinical accuracy, trust and safety, clinical trial monitoring, and expert data annotation for LLM builders.

What you will do

• Roleplay medical and health-related scenarios with AI agents.
• Evaluate the accuracy, clarity, safety, appropriateness, and potential harm of AI-generated health information.
• Red-team medical edge cases, unsafe guidance, model failure modes, and patient-risk scenarios.
• Identify signs of patient distress, medical risk, and urgency escalation.
• Develop medical rubrics, behavioral taxonomies, evaluation frameworks, and safety metrics.
• Document edge cases and failure patterns while collaborating with engineers, researchers, and clinicians.

Requirements

• Graduate-level training in medicine, nursing, public health, or a related clinical field.
• Clinical experience evaluating or managing acute, chronic, or complex medical conditions.
• 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, and ability to work with Slack, LLM tools, and Google Docs.
• Availability for up to 10 hours per week and occasional scheduled meetings; willingness to sign NDAs and handle sensitive or high-risk content.

Nice to have

• Completed degree and active licensure.
• 5+ years of clinical or applied medical experience.
• Experience in emergency medicine, primary care, specialty care, public health, health communication, or medical education.
• Experience with trust and safety, content moderation, medical data labeling, or clinical guidelines.
• Experience working across cultures or healthcare systems internationally, or interest in AI, NLP, or ML applications in healthcare.

Culture & Benefits

• Remote contract work supporting confidential AI safety and health information quality initiatives.
• Interdisciplinary collaboration with engineers, researchers, and clinicians.
• Work focused on patient safety, health equity, and responsible AI use in healthcare.
• Participation in review and calibration sessions with evolving, feedback-driven guidelines.