About the role
Senior Scientist-Principal Scientist-Antibody Protein Engineering Technology Portfolio Partnering News & Media
About Us Careers Contacts Back Senior Scientist-Principal Scientist-Antibody Protein Engineering Berkeley, CA Full Time High Throughput Discovery Apply Now The heart of Prellis Bio’s strategy is the combination of novel, cutting-edge methods in machine learning, biology at scale, and next-gen antibody discovery that address long-standing industry-wide problems in the drug development pipeline. Prellis Biologics uses proprietary technology to 3D print human lymph node organoids, enabling the rapid & diverse discovery of human antibody therapeutic candidates for a range of applications. To drive this forward, we are assembling an incredible team of discovery biologists, computational scientists, and protein scientists who want to make a difference to this important problem. Position Summary We are seeking a Senior / Principal Scientist — Antibody Protein Engineering to join our High Throughput Discovery group . You will drive antibody design and optimization, maturing early hits into development-ready leads. You will be responsible for: Leading late-stage antibody design and optimization — affinity maturation, Fc engineering, and developability polishing to advance lead candidates toward development. Building an integrated wet-lab + computational engineering platform — biologics reformatting, multispecific assembly, screening & library design (high-diversity libraries, focused-library maturation, ML training-data campaigns), and computational design. The ideal candidate will thrive in a dynamic, hands-on environment and play a critical role in delivering life-changing therapeutics.
Responsibilities Lead antibody engineering with a strong emphasis on late-stage design and optimization to refine and advance lead candidates toward development. Core activities:Reformat biologics across modalities (scFv, scFv-Fc, minibodies, Fab, VHH, Fc fusions, albumin fusions, TCRm) and assemble multispecifics (knob-in-hole, CrossMab, DVD-Ig, common LC, DARTs) Fc engineering — mutations for half-life, effector-function modulation, isotype selection, and bispecific heterodimerization Affinity maturation — design focused libraries to improve affinity, kinetics, and specificity Polishing & developability — remove chemical liabilities, mitigate aggregation and immunogenicity, humanize when needed Screening & library construction — design and execute campaigns (alanine scanning, high-diversity libraries via PCR, Gibson, mutagenesis, oligo-pool synthesis); generate ML training-data campaigns; translate manual workflows to automation Computational design — apply structural tools (PyMOL, Schrödinger BioLuminate / Maestro) and partner with Data Science / AI/ML on protein language and structure models (AlphaFold, ESM, RFdiffusion, ProteinMPNN, or equivalent)