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LatchBio

Cloud-based data platform for biotech R&D

AI Biologist - Drug Development

Translational Research & Bench BiologyUpdated on Nov 8
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • An advanced degree (MS, PhD, or PharmD) in pharmacology, toxicology, pharmaceutical sciences, medicinal chemistry, or a related biomedical field, or equivalent industry experience.
  • At least 3 years of hands-on experience in pharma or biotech drug discovery or development.
  • Direct experience with lead optimization, candidate nomination, or IND-enabling study design in at least one modality.
  • Experience interpreting PK/PD, ADME, and GLP toxicology data to inform dose selection and risk assessment.
  • Working knowledge of core pharmacology and toxicology study types, including GLP toxicology, safety pharmacology, genotoxicity, biodistribution, and bioanalytical assays.
  • Experience evaluating SAR, potency, selectivity, and developability trade-offs across candidate molecules.
  • Strong scientific writing skills to produce clear, evidence-supported rationale for drug-development decisions.
  • Proficiency in using AI agents and judgment to identify technically correct but pharmacologically or practically unsound model reasoning.
  • Comfort operating amid uncertainty and proactively flagging gaps in data or instructions.
  • High agency and initiative.

Responsibilities

  • Contribute to the technical approach for evaluating agent performance in reasoning across the drug discovery and development pipeline, from target validation through IND-enabling studies.
  • Work with software engineers and scientists to build datasets and AI agent tasks across the end-to-end drug-development pipeline.
  • Design realistic program case studies spanning target validation, lead optimization, candidate nomination, and IND-enabling studies across modalities.
  • Curate multimodal preclinical data bundles, including SAR and potency panels, ADME/PK profiles, in vivo efficacy, GLP toxicology, safety pharmacology, and biodistribution data.
  • Evaluate PK/PD, GLP toxicology, and safety pharmacology findings across modalities and development stages.
  • Reconstruct program go/no-go decisions from multisource data.
  • Review and stress-test agent outputs for pharmacological soundness, identifying reasoning that is textbook-correct but not defensible in a program review.
  • Calibrate AI agent confidence on preclinical data with incomplete or conflicting signals rather than forcing a binary decision.
  • Translate preclinical data into decisions that advance or terminate a program.

Desired Qualifications

  • Familiarity with IND-enabling regulatory requirements and the nonclinical data package expected by the FDA and EMA.

About the Company

LatchBio

Cloud-based data platform for biotech R&D

Latch.bio provides a cloud-based data platform for biotech companies to manage and analyze their data. It stores unlimited raw data, organizes and transforms it, and offers analysis tools, all in one place. The platform also includes workflow orchestration, so teams can set up analyses that automatically run across many computing cores and scale as needed, while the interface makes it easy to view analysis results and make quick decisions. A key feature is a customizable data platform that eliminates the need for separate infrastructure setup and supports strong security for large-scale data processing. Compared with competitors, Latch.bio positions itself as a single, cost-efficient solution that replaces multiple tools and optimizes cloud usage to reduce expenses. Its goal is to help biotech companies move projects forward faster by making data analysis cheaper, simpler, and more accessible.

Company size
51-200
Company stage
Series B
Total funding
$163M
Headquarters
San Francisco, CA
Founded
2021

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