Remote Medical Science Liaison — AI Training Evaluator

Alignerr Corp.; Dallas (TX); Remote; USD 14,000 - 55,000; Part time

Benefits offered by this job

Autonomy

Global collaboration

Flexible remote

Job summary

Alignerr Corp. is seeking experienced Medical Science Liaisons to help evaluate and improve AI systems trained on clinical and biomedical content.

This fully remote hourly contract is designed for working medical professionals who want flexible, task-based work and to contribute to cutting-edge AI projects. You will review AI outputs for accuracy, validate interpretation of clinical data, and provide expert feedback to improve medical datasets and AI reasoning.

Qualifications

• Background in medical affairs, clinical research, or scientific communications.
• Ability to interpret and communicate complex clinical data, publications, and regulatory materials.
• Experience in an externally facing medical role (MSL, clinical educator, scientific advisor).

Responsibilities

• Review and evaluate AI-generated clinical and biomedical content for accuracy and clarity.
• Validate how AI systems interpret and communicate clinical trial data and safety information.
• Identify errors, misrepresentations, or gaps in scientific reasoning within AI outputs.
• Provide structured expert feedback to help AI systems better serve healthcare professionals.
• Contribute to development of high-quality medical datasets and content evaluation frameworks.
• Work independently and asynchronously on task-based assignments.

Skills

MSL experience

Clinical data interpretation

Scientific writing

Analytical skills

External communication

Education

Clinical background

Job description

Alignerr Corp. is seeking experienced Medical Science Liaisons to help evaluate and improve AI systems trained on clinical and biomedical content.

This fully remote hourly contract is designed for working medical professionals who want flexible, task-based work and to contribute to cutting-edge AI projects. You will review AI outputs for accuracy, validate interpretation of clinical data, and provide expert feedback to improve medical datasets and AI reasoning.