About Perle
At Perle, we collaborate with leading healthcare and technology partners to develop advanced AI systems that help identify disease earlier and support better patient outcomes. High-quality clinical data—and the experts who can interpret it—are essential to this mission.
The Opportunity
We’re seeking Physicians, Dentists, and Pharmacists to join us as Clinical Data Annotation Specialists on a remote, project-based basis. In this role, your clinical expertise will directly influence the development of AI models used across large-scale healthcare partnerships.
If you're excited about applying your medical background in the world of cutting-edge health technology, this opportunity lets you make a meaningful impact from anywhere in the world—while opening the door to long-term career growth within clinical AI.
What You'll Do

• Annotate and label clinical data with accuracy, including symptoms, diagnoses, medications, patient histories, and clinical notes.
• Identify early disease indicators, capturing nuanced patterns that help AI systems understand health risks earlier.
• Validate data quality and ensure consistency across annotations.
• Work with Perle’s AI and product teams to refine annotation guidelines and create clinically meaningful labeling frameworks.
• Offer clinical interpretation for complex or ambiguous cases.
• Document your rationale clearly and consistently to support model reliability.
  

Qualifications

• A clinical degree in one of the following areas:
• • Medical (e.g., MBBS/MD)
  • Dental (e.g., BDS/DDS/DMD)
  • Pharmaceutical (e.g., BPharm/PharmD)
• Solid understanding of common clinical terms, diagnostics, and healthcare workflows.
• Ability to interpret real medical records with strong attention to detail.
• Comfort identifying early-stage disease patterns or subtle clinical risk factors.
• Strong written communication and dependable clinical reasoning.
• Ability to work independently and manage project-based tasks.
• Openness to feedback and evolving guidelines.
• Bonus points for: Experience in medical documentation, clinical research, healthcare analytics, or medical coding; Exposure to AI/ML projects or data annotation tools; Familiarity with EHR systems and structured/unstructured medical data.

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