Endocrinologist

Turing•New York, NY
•Remote

About The Position

In this project, the Endocrinologist will use their expertise in endocrinology to help fine-tune large language models. Their knowledge of hormonal disorders, metabolic diseases, and long-term endocrine management will help ensure AI systems provide accurate, empathetic, and safe medical reasoning. The role involves designing and solving advanced clinical scenarios, evaluating AI-generated responses, identifying knowledge gaps across endocrinology subspecialties, collaborating with AI researchers and medical peers, and providing structured expert feedback for AI development in clinical and educational applications. The engagement is fully remote and collaborative, requires 20–40 hours per week with a minimum of 4 hours per day and overlap with Pacific time, and is expected to last one month with a possible extension. It is offered as a contractor/freelancer engagement with no medical or paid leave.

Requirements

  • MD or equivalent.
  • Active practice within the last 3+ years.
  • Board certification or equivalent qualification in Endocrinology.
  • Strong grasp of endocrine medicine, including diabetes, thyroid disorders, adrenal pathology, pituitary diseases, and metabolic bone disease.
  • Skill in articulating complex medical reasoning in clear, patient-friendly language.
  • Excellent written and spoken English.
  • Availability for 20–40 hours per week, with a minimum of 4 hours per day and overlap with Pacific time.

Nice To Haves

  • Familiarity with digital medical tools.
  • Education from a top-tier institution, such as Harvard, Stanford, UCSF, or Oxford.

Responsibilities

  • Design and solve advanced clinical scenarios reflecting endocrinology practice, including complex diabetes management and thyroid, adrenal, and pituitary disorders.
  • Evaluate AI-generated responses for diagnostic accuracy, clinical judgment, and evidence-based reasoning in endocrine medicine.
  • Identify gaps in AI understanding across endocrinology subspecialties, including diabetes, bone metabolism, and reproductive endocrinology.
  • Collaborate with AI researchers and medical peers to improve model quality and reliability.
  • Provide structured expert feedback to inform AI development for clinical and educational applications.
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