Community Oncologist

Labela builds evaluation and training data for frontier AI labs by working with verified subject matter experts. We recruit physicians, scientists, and specialists to help improve AI model performance in complex, high-stakes domains.

Role

Labela is recruiting practicing community medical oncologists to contribute to AI training and evaluation projects. Contributors review, write, and assess AI-generated clinical content in oncology. They draw on their day-to-day experience treating patients in community settings to identify errors, ambiguity, unsafe recommendations, or gaps in clinical reasoning.

Requirements

• MD or DO with board certification in Medical Oncology (ABIM or AOBIM)
• Currently practicing medical oncology with an active patient caseload
• Practicing in a community setting, such as a private practice, community hospital, or non-academic health system
• No current affiliation with a university, academic medical center, or university hospital, including faculty appointments and academic staff positions
• Active, unrestricted medical license in the United States
• Strong working knowledge of current treatment guidelines (e.g., NCCN), systemic therapy regimens, toxicity management, and supportive care
• Ability to critically evaluate clinical reasoning, treatment plans, and supporting evidence
• Comfortable working independently on a computer-based platform

Note: This role is limited to medical oncologists. Radiation oncologists, surgical oncologists, and other specialties are not eligible for this project.

Responsibilities

• Evaluate AI model outputs for clinical accuracy, safety, and guideline concordance in oncology tasks
• Write or revise realistic patient cases, treatment scenarios, and clinical decision rationale that reflect community practice
• Give structured feedback on model errors, omissions, or recommendations that would be inappropriate in real-world care
• Complete calibration exercises so scoring stays consistent across contributors