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Pharmacology Expert - AI Trainer

Role overview

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, such as in vitro ADME and safety assays, PK/PD studies, CRO assay readouts, or LC-MS bioanalysis.
  • Comfortable using PK/PD or data analysis software and scientific AI tools.

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.
  • Evaluate AI model outputs and step-by-step reasoning on drug discovery tasks.
  • Develop specifications, grading rubrics, and verification processes for drug discovery data produced by external technical teams.

Key facts

Hard skills

Other skills

  • Communication
  • Collaboration

About the company

Mercor logo

Mercor

Job Boards & Talent Marketplaces

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

Company details

IndustryJob Boards & Talent Marketplaces
Company size51 - 200

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Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Drug Discovery Specialist, Pharmacology & ADME/Tox
Type: Contract
Compensation: $70–$100/hour
Location: Remote

Role 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. 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. Diagnose errors in scientific logic, tool usage, and factual accuracy. Provide clear, written technical feedback.
  • Develop specifications, grading rubrics, and verification processes for drug discovery data produced by external technical teams. 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.

Qualifications

Must-Have

  • 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, such as in vitro ADME and safety assays, PK/PD studies, CRO assay readouts, or LC-MS bioanalysis.
  • Comfortable using PK/PD or data analysis software and scientific AI tools.
  • 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.

Preferred

  • Experience with PK/PD or ADME modeling, writing grading rubrics, designing benchmark tasks, or evaluating scientific AI models.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



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Marcus Rivera

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