**Join a leading AI lab's cutting-edge research team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced LLMs.** # 1\. Overview Join a leading AI lab's cutting-edge research team and help build foundational AI models for science from the ground up.
About the role
Join a leading AI lab's cutting-edge research team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced LLMs.
# 1\. Overview
Join a leading AI lab's cutting-edge research team and help build foundational AI models for science from the ground up. We're seeking talented Drug Discovery subject-matter experts (SMEs), including pharmacologists, DMPK / ADME scientists and toxicologists from pharma, biotech, contract research or academic settings, to bring deep, hands-on discovery expertise to the design and evaluation of advanced AI models for drug discovery.
This is a part-time position through Cincinnatus LLC (or an appropriate international entity), with the opportunity to be placed at a leading AI Lab as part of their extended workforce.
# 2\. Key Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in mechanism of action, target and cellular pharmacology, ADME/Tox, and PK/PD.
- Design challenging, non-searchable drug discovery tasks, benchmarks and training data, and write accurate, well-structured solutions to problems such as interpreting assay readouts, identifying compound liabilities and planning optimization strategy.
- Evaluate AI model outputs and step-by-step reasoning on drug discovery tasks, diagnosing errors in scientific logic, tool usage and factual accuracy, and provide clear, written technical feedback.
- Develop specifications, grading rubrics and verification processes for drug discovery data produced by external technical teams, and act as the domain authority on data quality.
- Advise on assay design and quality control, experimental failure modes, and the biological and pharmacological validity of model outputs.
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
# 3\. Core Qualifications …
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