Remote Medical Science Liaison: AI Training & Validation

Alignerr Corp.; Ciudad de México; Presencial; MXN 1.466.000 - 2.933.000; A tiempo parcial

Descripción de la vacante

Alignerr Corp. is seeking experienced Medical Science Liaisons to train and validate AI systems in life sciences. You will translate complex clinical data into clear narratives and ensure AI understands biomedical information.

This is a remote freelance role with flexible scheduling and 10-40 hours per week. Ideal candidates will have MSL or clinical communications experience, strong data interpretation skills, and comfort working independently on structured review tasks.

Formación

• Background in medical affairs or scientific communications with experience engaging healthcare professionals.
• Strong ability to interpret and evaluate clinical data, medical publications, and regulatory materials.

Responsabilidades

• Review AI-generated medical and clinical content for scientific accuracy, clarity, and appropriateness for healthcare audiences.
• Validate AI outputs involving clinical trial data, safety information, pharmacology, and medical evidence.
• Identify errors, misrepresentations, or gaps in scientific reasoning and provide structured, actionable feedback.
• Help develop high-quality scientific communication examples that reflect real-world MSL standards.
• Work independently and asynchronously on task-based assignments.

Conocimientos

Medical affairs

Clinical data evaluation

Scientific communication

MSL experience

Educación

Advanced life sciences degree (PharmD/MD/PhD)

Herramientas

Data annotation tools

AI review workflows

Descripción del empleo

Alignerr Corp. is seeking experienced Medical Science Liaisons to train and validate AI systems in life sciences. You will translate complex clinical data into clear narratives and ensure AI understands biomedical information.

This is a remote freelance role with flexible scheduling and 10-40 hours per week. Ideal candidates will have MSL or clinical communications experience, strong data interpretation skills, and comfort working independently on structured review tasks.