Join OpenTrain as a Pharmacology AI Training Expert helping train and evaluate AI responses about pharmacokinetics, pharmacodynamics, drug interactions, and therapeutic use. Contract role, 20+ hrs/week, paid $60–$80/hr for experienced PharmD/PhD/MD candidates.
Medical & Health
100% Remote Hourly · $60–$80/hr
$60–$80/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 21, 2026
Posted
Open worldwide
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OpenTrain is the leading platform for people who build careers in AI training and data labeling. We connect skilled contributors with specialized projects, helping you consolidate opportunities, develop a portfolio, and grow a durable freelance career in a fast-growing field.
Why AI training matters
AI models learn from high-quality examples and expert feedback. Pharmacology-focused annotation and evaluation help ensure models give scientifically accurate, safe, and clinically relevant answers. This work is remote, flexible, and directly shapes how next-generation medical and health tools behave.
The role
You will review and improve pharmacology-related content to train and evaluate AI systems. Tasks combine expert review of AI-generated text, creation of scenarios and case studies, and documentation of the reasoning behind recommendations.
Contract, part-time work with a typical commitment of 20+ hours per week.
Paid on an hourly basis at $60–$80 USD per hour.
Work focuses on text: evaluation ratings and text-generation tasks.
What you'll do
Daily work is a mix of critique, content creation, and structured documentation. You will ensure scientific rigor and practical relevance in training materials and model responses.
Review pharmacological content for accuracy, clarity, and real-world relevance.
Create scenarios, case studies, and datasets tailored for pharmacology model training.
Evaluate AI-generated answers on pharmacokinetics, pharmacodynamics, drug interactions, and therapeutic applications.
Translate complex pharmacology concepts into clear, training-ready language.
Identify gaps or inaccuracies and propose data-driven improvements.
Document methodologies and the reasoning behind pharmacological recommendations.
Requirements
This role requires demonstrated pharmacology expertise and strong scientific communication. Prior AI or annotation experience is helpful but optional.
Advanced degree such as PharmD, PhD, MD, or equivalent in a pharmacology-related field.
Experience in clinical, molecular, or systems pharmacology.
Background authoring, reviewing, or teaching pharmacology content in academic, clinical, or industry settings.
Ability to evaluate drug interactions, pharmacokinetics, and pharmacodynamics accurately.
Strong analytical and critical evaluation skills and clear scientific writing.
Comfort providing structured, rationale-backed feedback on AI-generated pharmacology text.
Helpful background
Familiarity with global guidelines, regulatory standards, and best practices in drug therapy and safety will make you especially effective in this role.
Prior experience with guideline-based clinical recommendations or safety review is a plus.
Previous work with AI, data annotation, or educational content enhances readiness but is not required.
How work is organized
OpenTrain assigns tasks and evaluation workflows; you will perform rating and text-generation work using provided instructions and templates. Expect to document decisions and follow established annotation guidelines for transparency and reproducibility.
Labeling focuses on text evaluation (EVALUATION_RATING) and generating training text (TEXT_GENERATION).
This is a contractor position performed remotely and globally (English required).
Typical engagement: 20+ hours per week on a part-time contract basis.
Apply if you are
If you are an advanced pharmacology practitioner or researcher who wants to help shape safe, accurate medical AI, this role is an opportunity to apply your expertise remotely while contributing to cutting-edge model training.
You value clear scientific communication and enjoy translating complex ideas into teachable examples.
You can commit to the stated weekly time and prefer contract, part-time work paid hourly.
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