Anesthesiologist - MD expert

Job Summary

Join our customer’s team as a board-certified Anesthesiologist - MD expert, contributing your clinical expertise to a pioneering medical AI training project. In this remote, highly flexible role, you will collaborate with interdisciplinary teams to shape next-generation healthcare technologies by guiding AI model development and validation. This is a unique opportunity to have a direct impact on the advancement of safe, accurate, and accessible AI-driven care.

Key Responsibilities

Provide expert review, annotation, and labeling of diverse clinical anesthesia cases, encompassing all age groups and practice settings. Guide AI system development in multiple domains, including preventive care, chronic disease management, acute interventions, and pediatric anesthesia. Collaborate with multidisciplinary teams of clinicians, medical informaticists, and engineers to ensure AI solutions reflect holistic and evidence-based patient care. Design and validate clinical test cases, evaluating AI system outputs for clinical accuracy, safety, and usability. Contribute to the integration of clinical guidelines and best practices into medical AI training datasets. Clearly communicate clinical insights and feedback to drive iterative model improvements and enhance user trust in AI-driven solutions.

Required Skills and Qualifications

Medical Doctor (MD) degree with specialization in Anesthesiology and current, unrestricted license to practice. Board certification in Anesthesiology. Minimum of 4 years’ post-residency clinical experience, preferably in primary or community care settings. Demonstrated ability to interpret, synthesize, and annotate broad clinical and multidisciplinary medical knowledge into structured outputs. Outstanding written and verbal communication skills, with an emphasis on clarity, collaboration, and clinical precision. Deep interest in medical innovation, artificial intelligence, and advancing patient access through technology.

Preferred Qualifications

Prior involvement in digital health or clinical informatics projects. Experience with medical data annotation, labeling, or quality assurance processes. Familiarity with medical AI systems or technology-driven healthcare initiatives.