Senior/Principal Antibody Optimization Scientist

Prellis Biologics, Inc; Berkeley (CA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Flexible work model

Stock-based incentives

Health and welfare plans

Job summary

Prellis Biologics, Inc. in Berkeley, CA, is seeking a Senior / Principal Scientist to lead antibody optimization within the High Throughput Discovery group.

You will own display-based workflows, direct affinity maturation campaigns, and partner with Data Science/AI to streamline the DBTL loop. The ideal candidate has a PhD with 5+ years in antibody engineering, hands-on yeast/phage display, and experience with computational design tools such as AlphaFold, PyMOL, and PLMs.

Qualifications

• PhD plus extensive (5+ years) relevant experience in antibody engineering and optimization.

Responsibilities

• Lead antibody optimization and engineering with emphasis on affinity maturation and liability engineering.
• Build out yeast/phage display platforms across multiple formats (scFv, Fab, IgG, VHH).
• Design focused/diversified libraries and apply sequencing-based enrichment to refine candidates.
• Collaborate with Data Science/AI to move design-build-test-learn loops forward.
• Manage CRO/CDMO partnerships for production and characterization.

Skills

Antibody engineering

Display platforms

Computational design

High-throughput screening

FACS and flow platforms

NGS data analysis

Molecular cloning

Protein language models

AI/ML collaboration

Cross-functional leadership

Education

PhD in Biochemistry, Bioengineering, Molecular Biology, or related field

Tools

Yeast display

Phage display

Gibson/SSM/EP-PCR

NGS library prep

PyMOL

Schrödinger

AlphaFold/AlphaFold-Multimer

ProteinMPNN/PLMs

Job description

Prellis Biologics, Inc. in Berkeley, CA, is seeking a Senior / Principal Scientist to lead antibody optimization within the High Throughput Discovery group.

You will own display-based workflows, direct affinity maturation campaigns, and partner with Data Science/AI to streamline the DBTL loop. The ideal candidate has a PhD with 5+ years in antibody engineering, hands-on yeast/phage display, and experience with computational design tools such as AlphaFold, PyMOL, and PLMs.