Remote MSL: AI Medical Content Reviewer & Validator

Alignerr Corp.; Edmonton; Remote; CAD 55,000 - 110,000; Part time

Benefits offered by this job

Fully remote

Autonomy

Global collaboration

Job summary

Alignerr Corp. seeks experienced Medical Science Liaisons to help evaluate and improve AI systems trained on clinical and biomedical content. This remote hourly contract offers 10–40 hours per week and flexibility to work on your own schedule.

You will review AI-generated medical content for accuracy, validate clinical data interpretations, and provide expert feedback to strengthen AI reliability in life-science contexts.

Qualifications

• Background in medical affairs, clinical research, or scientific communications.
• Experience engaging healthcare professionals in a field-based or externally facing capacity.
• Strong ability to interpret clinical data, medical publications, and regulatory materials.
• Confident communicator who can translate complex science into clear, accurate language.
• Detail-oriented with a commitment to scientific integrity.

Responsibilities

• Review and evaluate AI-generated medical and clinical content for scientific accuracy, clarity, and appropriateness.
• Validate the interpretation of clinical trial data, safety information, and medical literature within AI outputs.
• Identify errors, unsupported claims, or misleading scientific narratives in AI-generated text.
• Provide structured, expert feedback to improve the quality and reliability of AI responses in life-science contexts.
• Help develop and refine scientific communication benchmarks used to train and evaluate AI models.
• Work independently and asynchronously on your own schedule.

Job description

Alignerr Corp. seeks experienced Medical Science Liaisons to help evaluate and improve AI systems trained on clinical and biomedical content. This remote hourly contract offers 10–40 hours per week and flexibility to work on your own schedule.

You will review AI-generated medical content for accuracy, validate clinical data interpretations, and provide expert feedback to strengthen AI reliability in life-science contexts.