Job Description

This role offers a unique opportunity to leverage your expertise in drug discovery or toxicology within an innovative, AI-driven life sciences environment. You will play a critical role in enhancing scientific reasoning systems that support drug discovery, safety assessment, and translational pharmacology. Your contributions will ensure that complex biological mechanisms and safety risk interpretations are accurately represented in the training of next-generation biomedical AI models. Key Responsibilities

• Scientific Data Annotation
  • Review and annotate datasets related to drug discovery, pharmacology, and safety biology.
  • Interpret experimental outputs from target biology studies, biochemical assays, cellular models, and safety screens.
  • Analyze relationships between compound structure, potency, selectivity, exposure, and toxicity signals.
  • Identify mechanistic explanations behind efficacy or toxicity findings across discovery experiments.
  • Distinguish meaningful biological signals from experimental artifacts, assay interference, or model limitations.
• Quality Review & Validation
  • Audit annotated scientific datasets for biological, pharmacological, and safety accuracy.
  • Validate structure–activity relationships (SAR), target engagement logic, and pharmacokinetic interpretations.
  • Evaluate AI-generated reasoning on drug mechanism, toxicity risk, and safety margins.
  • Ensure correct interpretation of dose-response relationships, exposure margins, and translational relevance.
• Methodology & Knowledge Contribution
  • Contribute to annotation guidelines for drug discovery workflows, structure–activity relationships (SAR), pharmacokinetics and ADME reasoning, toxicity mechanisms and safety pharmacology, and translational biology and target validation.
  • Provide expertise on how discovery teams balance potency, selectivity, safety, and developability.
  • Advise on classification of toxicity findings, safety signals, and risk assessment frameworks.
• Model Evaluation & Feedback
  • Review AI-generated reasoning traces involving drug mechanism of action, target biology interpretation, toxicity mechanisms and risk assessment, and pharmacokinetic and exposure modeling.
  • Assess whether conclusions logically follow from experimental evidence and biological context.
  • Provide structured feedback to improve scientific rigor, causal reasoning, and translational relevance in model outputs.
• Documentation & Training Support
  • Contribute to scientific standards documentation and training materials for model development.
  • Help define gold-standard examples of drug discovery reasoning and toxicity interpretation.
  • Support calibration workflows spanning pharmacology, toxicology, and translational biology domains.

Applicants should possess a PhD, PharmD, DVM, MD, or MS with significant industry experience in:

• Medicinal Chemistry
• Pharmacology
• Toxicology
• Chemical Biology
• Molecular Biology
• Pharmaceutical Sciences
• Biochemistry

Additionally, candidates should have 3–5+ years of hands-on experience in drug discovery or safety assessment, including:

• Drug discovery programs from target validation through lead optimization
• Structure–activity relationship (SAR) analysis
• Pharmacokinetics (PK) and ADME interpretation
• Toxicology and safety pharmacology studies
• Interpretation of in vitro and in vivo experimental data

Strong expertise in target biology and mechanism-of-action reasoning is essential.

This is a remote position with an hourly employment type.

The hourly compensation ranges from $70 to $100.

Applicants must have the legal right to work in the applicable location.

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