Preclinical R&D Scientist - Drug Development - AI Trainer

Mercor; New York (NY); On-site; USD 83,000 - 193,000; Part time

Job summary

Mercor, a venture-backed AI lab, seeks a hands-on preclinical R&D expert to guide AI-driven drug discovery efforts in NY. You will blend wet-lab and translational experience with data-driven model development to shape what the platform builds.

This role requires real-world experience across drug modalities, IND-enabling know-how, and the ability to work ~10 hours per week in a collaborative, fast-paced setting. Remote options are not specified; applicants in the NYC area encouraged.

Qualifications

• Hands-on preclinical R&D experience at a company with in-house drug assets.
• Experience across multiple drug modalities.
• Experience taking programs toward clinic/IND-enabling.
• Industry experience in biotech outside top-20 pharma.
• Ability to work ~10 hours/week in a fast-paced environment.

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 (target/modality selection, optimization, risk).
• Help define structure and quality standards for the client's dataset pipeline.
• Participate in expert discussions, interviews, and research engagements.

Skills

Preclinical R&D

Drug modalities

Translational biology

Data labeling/annotation

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.