Preclinical Drug Development AI Training Expert

About OpenTrain

OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. We connect experts with opportunities to help develop cutting-edge AI, while supporting contributors as they build a lasting professional profile in this fast-growing field.

Creating an OpenTrain account is free. For this contract, OpenTrain AI is recruiting experienced preclinical drug development professionals to contribute directly to advanced AI training work.

About AI Training Work

AI training is the human side of building artificial intelligence. Experts review examples, annotate technical information, and evaluate model responses so that AI systems can produce more accurate, useful, and scientifically grounded results.

Your subject-matter expertise can help shape AI platforms and physics-based foundation models used in chemistry, materials science, and drug discovery. This remote work offers flexible scheduling and the opportunity to contribute to how emerging AI systems are developed.

The Role

OpenTrain AI is seeking a Preclinical Drug Development AI Training Expert to support AI training focused on preclinical research and development. You will review and annotate real-world R&D data and model outputs, provide expert judgment on drug development decisions, and help establish quality standards for scientific datasets.

This is a remote, hourly contractor position. The default commitment is 40 hours per week, with a stated minimum time requirement of 20+ hours per week. The role is open worldwide and requires English-language communication.

• Employment type: Independent contractor, part-time
• Location: Remote, worldwide
• Language: English
• Pay: $85–$142 per hour
• Time commitment: 20+ hours per week; 40 hours per week by default

What You'll Do

You will apply practical preclinical R&D experience to the review, classification, and evaluation of scientific information. The work includes both structured annotation and expert discussions about how AI systems should understand drug development.

• Review technical materials and real-world R&D data within your area of expertise
• Label, classify, and annotate scientific data and AI model outputs
• Evaluate model outputs to help improve performance and scientific quality
• Provide expert perspectives on target and modality selection, optimization, trade-offs, and risk
• Help define structure and quality standards for a scientific dataset pipeline
• Participate in expert discussions, interviews, and research engagements

Required Qualifications

This opportunity is intended for experienced industry R&D professionals with hands-on, non-administrative preclinical experience. Your background must include work at a company that develops its own drug assets in-house and has taken programs to the clinic.

• At least 5 years of relevant industry R&D experience
• Experience in a core R&D function such as discovery biology, medicinal chemistry, protein or antibody engineering, computational research, in vivo or translational research, pharmacology or PK-PD, toxicology, or CMC/formulation
• Hands-on experience with one or more drug modalities, including small molecules, monoclonal antibodies, peptides, ADCs, bispecifics, mRNA, siRNA, ASOs, PROTACs, molecular glues, cell therapies, gene therapies, or radioligand therapies
• Ability to review and annotate scientific data and AI model outputs
• Strong ability to communicate expert perspectives in discussions and research engagements
• Hands-on preclinical R&D experience at a company whose programs have progressed to the clinic

Helpful Background

Experience across the drug development lifecycle will help you contribute meaningful context to model evaluation and dataset design. Background in a range of biotech environments is particularly relevant.

• Experience taking a program through lead optimization or IND-enabling/preclinical development
• Experience at a mid-sized, emerging, or resource-constrained biotechnology company
• Current experience outside the top 20 pharmaceutical companies is especially relevant

Why Contribute to AI Training

Every major AI system depends on people who can prepare, review, and evaluate high-quality examples. By contributing your preclinical drug development expertise, you can help guide systems operating at the intersection of biology, chemistry, and computational discovery while working remotely on a flexible contract.

• Work remotely from anywhere in the world
• Choose a schedule that fits a 20+ hour weekly commitment
• Apply specialized industry expertise to frontier AI development
• Build experience in the rapidly growing AI training industry