Tech Stack

Description

You will bridge computational design and experimental validation in our antibody discovery engine. You'll serve as the primary liaison between wet-lab and ML teams, driving the Design-Build-Test-Learn cycle to enable rational, data-driven biologic drug discovery.

Requirements

• Ph.D. in molecular biology, biochemistry, or related field
• 8+ years post-PhD experience in antibody/protein engineering
• Experience working with data scientists and ML engineers
• Hands-on proficiency with structural modeling and ML protein design tools
• Expert knowledge of antibody structure-function and rational design

Responsibilities

• Serve as primary liaison between wet-lab antibody team and ML team
• Drive Design-Build-Test-Learn cycle for antibody discovery
• Translate computational designs into experimental workflows
• Ensure computational predictions are validated and data retrains models
• Champion rational, data-driven approach to biologic drug discovery