Senior Scientist, Computational Antibody Design

Genentech; San Francisco (CA); On-site; USD 168,000 - 312,000; Full time

Benefits offered by this job

Discretionary annual bonus

Genentech benefits package

Job summary

Genentech, California, is seeking a Senior Scientist to accelerate antibody discovery by applying developability and biophysical modeling with ML methods. You will work with gRED/pRED scientists on active portfolio projects and translate computational predictions into actionable guidance for antibody engineering teams.

The role emphasizes collaboration across disciplines, advancement of method development, and transitioning research into production-ready components, with a discretionary annual

Qualifications

• PhD or equivalent with 5–8 years in ML/computational methods or biophysics.
• Strong expertise in developability, biophysical modeling, or antibody engineering.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• First-author publications or evidence of research contributions.
• Experience with molecular modeling tools and biophysical analysis.

Responsibilities

• Apply developability modeling to active portfolio projects in gRED and pRED, translating computational predictions into actionable guidance for antibody engineering teams
• Support the continuation and evolution of our molecular assessment research efforts in partnership with Antibody Engineering stakeholders, ensuring continuity and quality of ongoing work
• Interface with portfolio scientists and stakeholders to understand their scientific challenges and translate those into computational approaches; clearly communicate model outputs and limitations
• Contribute to method development in developability prediction, biophysical modeling, and ML model improvement—identifying gaps in our current approaches and proposing solutions
• Work with our modeling and platform teams to transition research‑stage models into production‑ready components that can be reliably used on portfolio projects
• Develop technical relationships and credibility with gRED/pRED stakeholders, establishing yourself as a trusted resource for computational support in antibody design

Skills

Python

ML frameworks

Developability modeling

Biophysical modeling

Antibody engineering

Publications

Education

PhD in Computational Biology, Biophysics, Chemistry, or related field

Equivalent advanced experience (5-8 years in ML/computational methods or biophysics)

Tools

Molecular modeling tools

Biophysical analysis tools

Job description

Genentech, California, is seeking a Senior Scientist to accelerate antibody discovery by applying developability and biophysical modeling with ML methods. You will work with gRED/pRED scientists on active portfolio projects and translate computational predictions into actionable guidance for antibody engineering teams.

The role emphasizes collaboration across disciplines, advancement of method development, and transitioning research into production-ready components, with a discretionary annual