Medical Science Liaison (MSL)

Alignerr Corp.

Dallas (TX)

Remote

USD 14,000 - 55,000

Part time

8 days ago

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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

Medical Science Liaison (MSL) — AI Training
About The Role

We're looking for experienced Medical Science Liaisons to help evaluate and improve AI systems being trained on clinical and biomedical content. Your scientific expertise will directly shape how AI understands, communicates, and reasons about medical evidence — making a real impact on the future of healthcare AI.

This is a fully remote, flexible contract role designed for working medical professionals, clinical researchers, and scientific communicators who want to contribute to cutting-edge AI projects on their own schedule.

  • Organization: Alignerr
  • Type: Hourly Contract
  • Location: Remote
  • Commitment: 10–40 hours/week
What You'll Do
  • Review and evaluate AI-generated clinical and biomedical content for accuracy, scientific integrity, and clarity
  • Validate how AI systems interpret and communicate clinical trial data, medical evidence, 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 the development of high-quality medical datasets and content evaluation frameworks
  • Work independently and asynchronously on task-based assignments
Who You Are
  • Background in medical affairs, clinical research, or scientific communications
  • Proven ability to interpret and communicate complex clinical data, publications, and regulatory materials
  • Experience in an externally facing medical role — MSL, clinical educator, scientific advisor, or similar
  • Strong scientific writing and analytical skills
  • Detail-oriented with a commitment to accuracy and evidence-based reasoning
  • No prior AI or data annotation experience required
Nice to Have
  • Prior experience with data annotation, content evaluation, or quality review workflows
  • Familiarity with AI tools or language model evaluation
  • Experience across multiple therapeutic areas
Why Join Us
  • Work on cutting-edge AI projects alongside top life-science and research organizations
  • Fully remote and flexible — work on your own schedule, from anywhere
  • Freelance perks: autonomy, variety, and global collaboration
  • Contribute to meaningful work that advances the quality and safety of medical AI
  • Potential for ongoing work and contract extension
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