Health Policy & Management - AI Content Specialist

About the role

Your public health expertise is more valuable than ever — and not just in traditional settings. At Alignerr, we partner with the world's leading AI research labs to build smarter, safer, and more accurate AI models. We're looking for Masters-level public health professionals to help train and evaluate large language models (LLMs) on complex health policy, epidemiology, and population health topics. This is a rare opportunity to apply your graduate-level knowledge in a cutting-edge AI context, work entirely on your own schedule, and make a direct impact on how AI communicates health information to the world.

Responsibilities

• Design Complex Public Health Scenarios — Create advanced prompts and case studies involving disease outbreak simulations, health equity assessments, social determinants of health, and statistical interpretation of clinical trial data.
• Author Ground-Truth Solutions — Write rigorous, step-by-step model responses that synthesize peer-reviewed research, epidemiological evidence, and current public health guidelines (CDC, WHO, and other authoritative sources).
• Audit AI-Generated Health Content — Evaluate AI outputs for accuracy, bias, logical consistency, and adherence to ethical health communication standards. Identify misinformation, unsupported claims, and gaps in reasoning.
• Sharpen AI Reasoning — Provide structured, expert feedback that helps models distinguish correlation from causation, communicate health risks clearly, and adapt messaging for diverse populations.

Requirements

• Hold a Master of Public Health (MPH), Master of Science in Public Health (MSPH), or a closely related graduate degree.
• Strong foundational knowledge in at least two areas: Epidemiology, Biostatistics, Environmental Health, or Health Policy.
• Can translate complex health data into clear, accurate, and culturally sensitive written communication.
• Detail-oriented — comfortable checking statistical significance, evaluating data citations, and assessing the logic of health interventions.

Qualifications

• No prior AI experience required — your domain expertise is what matters.
• Nice to have: Experience with data annotation, quality evaluation, or research coordination; Proficiency with data analysis tools such as R, SAS, or Stata; Background in health communication, clinical research, or public health surveillance; Familiarity with AI systems or content evaluation workflows.