Oncologist (Train AI Models Part Time!)

hackajob is collaborating with Mercor to connect them with exceptional professionals for this role. 1\. Role Overview Mercor is collaborating with a leading AI research lab on a project to advance frontier medical problem-solving in oncology. We are looking for actively practicing oncologists based in the United States with hands-on experience in clinical trials. The goal of this project is to identify gaps in AI model reasoning around real-world oncology cases, particularly in clinical trial design, patient eligibility, and treatment decision-making, and to support the training of cutting-edge AI models. This is a short-term, high-impact, remote opportunity for oncologists excited about applying their clinical expertise to frontier AI research, with the possibility of extension based on performance. 2\. Key Responsibilities \- Create realistic, nuanced oncology tasks and scenarios, particularly around clinical trials, that expose weaknesses in frontier AI model responses \- Evaluate AI-generated clinical reasoning for accuracy, completeness, and alignment with current standard-of-care guidelines \- Identify flawed logic, missed diagnoses, incomplete treatment rationale, or unsafe recommendations in model outputs \- Provide clear, well-structured expert responses and chain-of-thought reasoning that reflect real clinical decision-making \- Maintain high standards of clinical rigor and accuracy throughout all contributions 3\. Required Qualifications You are a strong fit for this project if you meet all of the following: \- MD or DO with a completed fellowship in medical oncology or hematology/oncology \- Active, unrestricted US medical license \- Currently practicing in the United States and seeing oncology patients \- 3 years of post-fellowship experience in your current role strongly preferred \- Active involvement in or direct experience with oncology clinical trials (ast a PI, sub-investigator, or treating physician) Not in scope for this project: radiation oncology, surgical oncology, oncology no in clinical practice. Other qualifications: \- Deep familiarity with clinical trial protocols, eligibility criteria, and regulatorB, FDA, RECIST criteria) \- Ability to articulate clinical reasoning clearly and precisely in written form \- Strong attention to detail in evaluating the accuracy and safety of AI-generated me 4\. Application & Onboarding \- Credential verification: license status, fellowship completion, and current practice \- Final roster placement is confirmed with the project team before your start dateaa415a4b-8b21-40fc-a65c-70d2b25ca29a