Technical Development Principal Scientist - Computational Biophysics
Genentech · South San Francisco, CA · Manufacturing & Engineering
About this role
Genentech is hiring a principal-level Research Scientist in the machine learning function based in South San Francisco, CA. The posting calls out experience with Python, C, Bash. Compensation is listed at $120,800–$224,300 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- principal
- Track
- Individual contributor
- Employment
- Full-time
- Location
- South San Francisco, CA
- Department
- Manufacturing & Engineering
- Posted
- Apr 2, 2026
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Job description
from Genentech careersThe Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche!
As part of Pharma Technical Development (PTD) our organization is committed to deliver the Pharma ambitions by bringing game-changing therapies from clinical phase I into the market to serve every patient, every day. Our core business is to develop safe, innovative and effective drugs using cutting edge technologies for manufacturing process (Drug Substance and Drug Product), clinical supply, formulation, device, packaging, and analytical development.
As an integrated partner within the drug development ecosystem, Global Biologics Pharmaceutical Development is dedicated to effectively developing innovative and patient-centered parenteral drug products including Formulation and Process Development, and Drug Delivery Systems.
The OpportunityAre you passionate about Computational Biophysics of proteins and looking for a meaningful role? We seek a creative, highly motivated scientist with a background in computational biophysics to join the Pharmaceutical Development Department in US-Pharma Technology Development.
The Scientist will focus on evaluating, developing and employing a variety of in silico methods and workflows to support the development of biologics.