Pharmaceutical R&D Expert - Fully Remote

Mercor; Greater London; Remote; GBP 83,000 - 124,000; Part time

Job summary

Mercor is partnering with a venture-backed AI lab building frontier AI platforms for chemistry and drug discovery. We seek hands-on preclinical R&D experts across drug modalities to guide what we build and to bridge wet-lab work with AI-driven data insights.

The role blends bench science with translational experience, contributing to data curation, model training, and critical development decisions. This is a part-time engagement (~10 hours/week) in a fast-evolving biotech setting.

Qualifications

• Hands-on preclinical R&D experience in a company that develops its own drug assets and has taken programs to the clinic.
• Experience across discovery biology, medicinal chemistry, protein/antibody engineering, computational, in vivo/translational, pharmacology/PK-PD, toxicology, or CMC/formulation is valued.
• Experience with one or more drug modalities (small molecules, antibodies, peptides, ADCs, mRNA, etc.) is a plus.

Responsibilities

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

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.

Are you a preclinical R&D scientist who has taken drug programs from the bench toward the clinic — and curious how AI is reshaping drug discovery? This is a hands-on role that blends your wet-lab and translational experience with a growing understanding of how scientific data trains the next generation of AI models.

In this role, you'll:

• 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 (target/modality selection, optimization, trade-offs, risk)

• Help define structure and quality standards for the client's dataset pipeline

• Participate in expert discussions, interviews, and research engagements

You're a strong fit if you:

• Have hands-on, non-administrative preclinical R&D experience at a company that develops its own drug assets in-house and has taken programs to the clinic — Must Have

• Work in a core R&D function: discovery biology, medicinal chemistry, protein/antibody engineering, computational, in vivo/translational, pharmacology/PK-PD, toxicology, or CMC/formulation — Must Have

• Have hands-on experience with one or more drug modalities (small molecules, monoclonal antibodies, peptides, ADCs, bispecifics, mRNA, siRNA, ASOs, PROTACs, molecular glues, cell therapies, gene therapies, radioligand therapies, etc.) — Must Have

• Have 5+ years of relevant industry R&D experience (flexible based on depth)

• Have taken a program through lead optimization or IND-enabling/preclinical development (nice to have)

• Have experience at mid-sized, emerging, or resource-constrained biotech — ideally currently outside the top-20 pharmaceutical companies (nice to have)

This is a hands-on preclinical R&D role — likely not the right fit if your work is mainly CRO/CDMO services, academic-only, QC/analytical-only, clinical-development-only, diagnostics, or regulatory/medical-writing.

Your work will directly feed into the models reshaping how medicines are discovered, helping intelligent systems reason about real-world pharmaceutical R&D.

Here are more details about the role:

• You will interface directly with the client team.

• This is an ongoing, part-time engagement of roughly 10 hours per week.

• Seniority welcome from individual contributor through Director.