AI-Driven Preclinical R&D Scientist for Drug Discovery

Obsidian; San Francisco (CA); On-site; USD 165,000 - 248,000; Part time

Job summary

Mercor is partnering with a venture-backed AI lab building frontier AI platforms and physics-based foundation models for chemistry, materials science, and drug discovery. They're extending their platform into new areas of pharmaceutical development and are looking for hands-on preclinical R&D experts across drug modalities to help guide what they build.

In this role, you'll blend wet-lab and translational experience with growing AI modeling insight, review technical materials and real-world

Qualifications

• Hands-on, non-administrative preclinical R&D experience at a company with in-house drug assets.
• Experience across multiple drug modalities (e.g., small molecules, antibodies, biologics, etc.).
• 5+ years of relevant industry R&D experience (flexible based on depth).
• Experience taking a program through lead optimization or IND-enabling/preclinical development (nice to have).
• Experience at mid-sized, emerging biotech (nice to have).

Responsibilities

• Review technical materials and real-world R&D data in your area of expertise.
• Label, classify, and annotate scientific data and model outputs to improve model performance.
• Provide expert perspective on key scientific and development decisions.
• Help define structure and quality standards for the dataset pipeline.
• Participate in expert discussions, interviews, and research engagements.

Skills

Preclinical R&D

Data labeling

Translational science

AI in drug discovery

Job description

Mercor is partnering with a venture-backed AI lab building frontier AI platforms and physics-based foundation models for chemistry, materials science, and drug discovery. They're extending their platform into new areas of pharmaceutical development and are looking for hands-on preclinical R&D experts across drug modalities to help guide what they build.

In this role, you'll blend wet-lab and translational experience with growing AI modeling insight, review technical materials and real-world