Pharmacology Expert - AI Trainer

Mercor; Seattle (WA); On-site; USD 83,000 - 138,000; Part time

Job summary

Mercor is seeking a Pharmacology SME to join a cutting-edge AI lab's research team, focusing on drug discovery data, ADME/Tox, PK/PD, and mechanism of action. This is a part-time engagement through an international partner, with placement at a leading AI Lab.

The role requires a PhD in a related field, 3+ years in early drug discovery, hands-on data analysis, and the ability to contribute at least 20 hours per week on weekdays. No coding is required, and strong written communication is essential.

Qualifications

• PhD in pharmacology, pharmaceutical sciences, toxicology, DMPK, biochemistry or a closely related discipline, or equivalent research experience.
• 3+ years of experience in early-to-mid stage drug discovery, pharmacology, DMPK/ADME or toxicology at a recognized organization.
• Hands-on experience analyzing experimental drug discovery data and using it to guide compound decisions.
• Comfortable using PK/PD or data analysis software and scientific AI tools (no coding required).
• Ability to engage reliably for at least 20 hours/week during weekdays.
• Strong written communication skills and the ability to explain complex technical decisions clearly.
• Nice to have: experience with PK/PD or ADME modeling, writing grading rubrics, designing benchmark tasks, or evaluating scientific AI models.

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.

Skills

Written communication

Work availability 20 hours/week

No coding required

Pharmacology domain expertise

Data analysis software proficiency

Education

PhD in pharmacology or related field

Tools

PK/PD analysis software

Scientific AI tools

Job description

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

• PhD in pharmacology, pharmaceutical sciences, toxicology, DMPK, biochemistry or a closely related discipline, or equivalent research experience.
• 3+ years of experience in early-to-mid stage drug discovery, pharmacology, DMPK / ADME or toxicology at a recognized organization, such as a pharmaceutical or biotech company, a contract research organization, or an academic drug discovery group.
• Hands-on experience analyzing experimental drug discovery data, such as in vitro ADME and safety assays, PK/PD studies, CRO assay readouts or LC-MS bioanalysis, and using it to guide compound decisions.
• Comfortable using PK/PD or data analysis software and scientific AI tools (no coding required).
• Ability to engage reliably for at least 20 hours/week during weekdays.
• Strong written communication skills and the ability to explain complex technical decisions clearly.
• Nice to have: experience with PK/PD or ADME modeling, writing grading rubrics, designing benchmark tasks, or evaluating scientific AI models.

About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus, or an appropriate international entity, serves as the employer of record for these engagements, providing employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives.

Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.