Turing
Evaluate and enhance large language model outputs in the medical domain with a focus on dermatology by assessing AI-generated clinical content for accuracy, safety, and relevance. Collaborate with AI researchers and clinicians to ensure model performance aligns with evidence-based dermatology standards.
Key Responsibilities
- • Review AI-generated medical text for accuracy, harmfulness, and completeness, with focus on dermatology.
- • Evaluate diagnoses, treatment plans, and summaries for dermatologic cases.
- • Provide expert feedback to improve medical integrity and safety of LLM outputs.
- • Collaborate with AI researchers and clinicians to align model performance with evidence-based dermatology standards.
Required
- • MD/DNB (Dermatology) or equivalent postgraduate qualification with valid medical license.
- • Minimum 5 years of post-residency experience in dermatology.
- • Strong command of English for interpreting clinical content and guidelines.
- • Excellent analytical and critical thinking skills with focus on patient safety and accuracy.
Preferred
- • Experience in medical content review, clinical research, annotation or AI/ML evaluation preferred.
- • Familiarity with global dermatology guidelines (e.g., AAD, BAD, IADVL) is a plus.
Benefits & Perks
- • Work on the cutting edge of AI.
- • Fully remote and flexible work environment.
- • Exposure to advanced LLMs and insight into how they’re trained.
Company Overview
Industry: Healthcare Technology
Company Size: 500-1,000 employees
Founded: 2015
Headquarters: San Francisco, CA
Company Links
Key Contacts
Contact information not available
About the Company
Leading healthcare technology company focused on improving patient outcomes through innovative digital solutions. We're transforming the way healthcare is delivered with cutting-edge technology and data-driven insights. Our platform serves over 10,000 healthcare professionals and has processed millions of patient interactions.
Recent News & Updates
About Turing:
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.
Role Overview:
We are seeking an experienced Dermatologist to help evaluate and enhance large language model (LLM) outputs in the medical domain. You’ll assess AI-generated clinical content for dermatological accuracy, safety, and relevance — contributing to the development of responsible AI in healthcare.
What You'll Do Day-to-Day:
- Review AI-generated medical text for accuracy, harmfulness, and completeness, with focus on dermatology.
- Evaluate diagnoses, treatment plans, and summaries for dermatologic cases.
- Provide expert feedback to improve medical integrity and safety of LLM outputs.
- Collaborate with AI researchers and clinicians to align model performance with evidence-based dermatology standards.
Requirements:
- MD/DNB (Dermatology) or equivalent postgraduate qualification with valid medical license.
- Minimum 5 years of post-residency experience in dermatology.
- Strong command of English for interpreting clinical content and guidelines.
- Excellent analytical and critical thinking skills with focus on patient safety and accuracy.
- Experience in medical content review, clinical research, annotation or AI/ML evaluation preferred.
- Familiarity with global dermatology guidelines (e.g., AAD, BAD, IADVL) is a plus.
Perks of Freelancing with Turing:
- Work on the cutting edge of AI.
- Fully remote and flexible work environment.
- Exposure to advanced LLMs and insight into how they’re trained.
Offer Details:
- Engagement type : Contractor assignment/freelancer (no medical/paid leave)
- Duration: 1 week
Evaluation Process:
- Shortlisting based on qualifications and one round of interview.
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