Doctors and Medical Experts – AI Research

Role Overview

• Data labeling and curation: Review clinical notes, audio, videos and other modalities, identifying relations and reasoning steps per guidelines.
• LLM and model evaluations: Run structured evals (human-in-the-loop) to assess accuracy, safety, clinical relevance and clinical reasoning of models.
• Prompting and prompt-engineering: Design, test, and iterate prompts to improve performance and reliability.
• Fine-tuning support: Create high-quality instructions/responses and explore edge-case datasets to enhance models.
• Feedback and error analysis: Identify critical/failure points, propose strategies to help mediate and document findings.
• Scoring/Rubrics frameworks: Develop and refine scoring rubrics for quality assurance (e.g., accuracy, clarity, safety, completeness, guideline adherence).
• Guideline refinement: Collaborate with researchers to improve annotation standards, acceptance criteria, and evaluation protocols.

Requirements

• Doctor based in the UK with an active GMC license.
• Native or near-native fluency in English (spoken and written).
• Good understanding of clinical terminology, tools and workflows.
• Excellent summarisation and written communication skills.
• Strong attention to detail and commitment to clinical accuracy.
• Comfortable working independently in an asynchronous environment.

Benefits

• Remote work
• Asynchronous and flexible scheduling, allowing you to balance work with clinical practice or studies.
• Competitive compensation based on experience.
• The opportunity to influence and enhance AI tools that serve healthcare professionals.
• Experience working at the intersection of medicine and AI, helping shape the future of healthcare.
• Opportunity to collaborate with clinicians and AI researchers to deepen your own clinical acumen and professional expertise in AI within healthcare.