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Collate

AI-driven documentation automation for life sciences

AI Research Scientist

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$188k - $350k /yrIn-person

About the Job

Requirements

  • A strong background in machine learning, natural language processing, or related fields, with publications or equivalent experience.
  • Ability to balance theoretical complexity with the simplicity of maintaining and improving real-world AI applications in life sciences.
  • Experience troubleshooting natural-language-processing performance gaps and improving applications using online and offline evaluation.
  • Hands-on experience building and experimenting with deep learning models such as PyTorch, JAX, or TensorFlow.
  • Ability to bridge theory and practice, from new research ideas to real-world deployments.
  • Motivation to apply AI research in life sciences, where rigor, safety, and impact matter.

Responsibilities

  • Explore large language model prompt optimization, robustness of large language model applications, and modeling approaches in machine learning, natural language processing, and reasoning.
  • Prototype and validate AI capabilities that expand the product roadmap.
  • Collaborate with engineering, product, and design to bring research into production.
  • Develop evaluation frameworks to measure safety, reliability, and fairness.
  • Share findings with the broader AI community through publications and open collaboration.
  • Help shape the long-term research agenda.

Desired Qualifications

  • Experience in translation is an added bonus.

About the Company

Collate

AI-driven documentation automation for life sciences

Collate provides an AI-powered platform that automates and streamlines the creation of documentation for drug development, medical devices, and diagnostics, reducing time and resources spent on regulatory paperwork. The platform auto-generates, organizes, and governs documents while offering data discovery and observability to ensure high-quality, compliant data assets. It differentiates itself by delivering end-to-end documentation and data governance for life sciences in one platform that covers drugs, devices, and diagnostics, minimizing manual work. Its goal is to accelerate bringing life-saving innovations to patients by shortening development and regulatory timelines so researchers can focus on discovery.

Company size
11-50
Company stage
Series B
Total funding
$125M
Headquarters
San Francisco, CA
Founded
2025

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