Senior/Principal Antibody Engineer — High-Throughput Discovery

Initial Therapeutics, Inc.; Berkeley (CA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) plan

Flexible work models

Job summary

Prellis Bio in Berkeley, CA seeks a Senior/Principal Scientist — Antibody Protein Engineering to drive late-stage antibody design and optimization. You will mature hits into development-ready leads while building an integrated wet-lab and computational engineering platform.

The ideal candidate thrives in a hands-on, cross-functional setting, mentoring researchers and collaborating with data science on protein language models and structural tools.

Qualifications

• Ph.D. in Biochemistry, Bioengineering, Molecular Biology, Protein Engineering, or related field with equivalent industry experience (Sr. Scientist or Principal Scientist).
• Hands-on biologics reformatting across multiple modalities and Fc engineering.
• Experience optimizing antibody lead candidates (affinity, developability, Fc properties).
• Experience with high-content screening and data-driven design is preferred.

Responsibilities

• Lead late-stage antibody design and optimization to advance leads toward development.
• Build an integrated wet-lab + computational platform for design, screening, and library construction.
• Manage external CROs/CDMOs for biologics production and characterization.
• Collaborate with Data Science/AI teams on protein language models and structure predictions.

Skills

Antibody engineering

Biologics reformatting

Computational design

Cloning & mutagenesis

Education

Ph.D. in Biochemistry/Bioengineering/Molecular Biology or related field

Tools

PyMOL

Schrödinger BioLuminate/Maestro

Protein language models (ESM/RFdiffusion/ProteinMPNN)

Job description

Prellis Bio in Berkeley, CA seeks a Senior/Principal Scientist — Antibody Protein Engineering to drive late-stage antibody design and optimization. You will mature hits into development-ready leads while building an integrated wet-lab and computational engineering platform.

The ideal candidate thrives in a hands-on, cross-functional setting, mentoring researchers and collaborating with data science on protein language models and structural tools.