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AI Vaccine Formulation Optimization Engineer

James Yamamoto

Full-time · Job · Los_Angeles

About the role

We serve pharmaceutical R&D teams racing to cut years off vaccine development timelines. Our platform models antigen stability and adjuvant interactions before a single vial reaches the lab bench. In this role you'll design predictive models that rank candidate formulations by stability, immunogenicity potential, and manufacturability, working directly with wet-lab scientists to validate every prediction against real assay data. We publish internally and encourage conference submissions — expect to read papers, replicate findings, and push several of your own experiments into production models that guide which formulations move forward.

Responsibilities

  • Build predictive models ranking candidate vaccine formulations by stability and immunogenicity
  • Partner with wet-lab scientists to validate model predictions against assay results
  • Design feature pipelines from experimental and literature-derived data
  • Read and replicate relevant research papers, adapting findings into production models
  • Present findings in internal research reviews

Requirements

  • Strong background in applied machine learning, ideally in life sciences or chemistry
  • Experience with PyTorch and scikit-learn for predictive modeling
  • Comfortable working with noisy, small experimental datasets
  • Familiarity with statistical methods for uncertainty quantification

Benefits

  • Fully remote position
  • Equity in a Series B biotech AI company
  • Health, dental, and vision insurance
  • Annual research conference budget
  • Flexible PTO

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch scikit-learn statistics aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch scikit-learn statistics aws

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