Pharmaceutical R&D AI Specialist

Weekday AI

1d • Remote

About The Position

This role is for one of our clients. We are partnering with leading AI labs on our Project - an initiative to build realistic enterprise environments where advanced AI agents are trained and evaluated. We are seeking experienced pharmaceutical research professionals from top pharma, biotech organizations, and leading academic research centers to recreate real-world digital workspaces and design complex tasks that reflect actual R&D workflows. In this role, you will leverage your expertise across drug discovery, preclinical/translational research, clinical development, or regulatory/CMC to simulate high-fidelity pharma environments and contribute directly to shaping how next-generation AI systems operate in regulated research settings.

Requirements

• Advanced degree (PhD, MD, PharmD, or MS with significant experience); industry fellowship training is a plus
• 3+ years of full-time experience in a pharmaceutical, biotech, or leading academic research environment
• Expertise in one or more of the following areas: Drug discovery (medicinal chemistry, biology, HTS, DMPK), Preclinical / translational research (PK/PD, toxicology, biomarkers), Clinical development (Phase I–IV, biostatistics, clinical operations), Regulatory affairs (IND, NDA, BLA, EMA) or CMC, Real-world evidence, HEOR, or pharmacovigilance
• Hands-on experience with industry-standard tools and platforms (e.g., clinical data systems, modeling software, lab management tools)
• Strong analytical thinking and ability to translate complex workflows into structured task designs
• Excellent written communication and attention to detail

Responsibilities

• Build realistic digital workspaces that mirror day-to-day pharma R&D environments, including study protocols, investigator brochures, IND/NDA drafts, pharmacology reports, biomarker analyses, CMC documentation, and internal communications
• Design multi-step, workflow-driven tasks that require navigating multiple tools, datasets, and stakeholders
• Incorporate commonly used platforms (e.g., clinical trial systems, molecular modeling tools, electronic lab notebooks) into task environments
• Collaborate with peer experts to validate realism, rigor, and relevance of scenarios
• Work asynchronously with research teams to refine task structures and evaluation frameworks
• Contribute to benchmarking and improving AI systems used in pharmaceutical research

What This Job Offers

• Career Level: Senior