Remote Endocrinologist

Turing•San Francisco, CA

4d•Remote

About The Position

In this project, the Endocrinologist will apply expertise in endocrinology to fine-tune large language models. The role uses knowledge of hormonal disorders, metabolic diseases, and long-term endocrine management to help ensure AI systems provide accurate, empathetic, and safe medical reasoning. The work involves creating and solving advanced clinical scenarios, evaluating AI-generated medical responses, identifying knowledge gaps across endocrine subspecialties, collaborating with AI researchers and medical peers, and providing structured expert feedback to inform AI development for clinical and educational applications. This is a fully remote contractor/freelancer engagement for one month, with a possible extension, requiring 20–40 hours per week and at least four hours per day with overlap in PST.

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.
Ability to articulate complex medical reasoning in clear, patient-friendly language.
Excellent written and spoken English.
Commitment of 20–40 hours per week, with a minimum of four hours per day and overlap in PST.

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 next-generation AI development for clinical and educational applications.