Senior​/Principal Scientist- Antibody Optimization and Engineering

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 Optimization and Engineering to join our High Throughput Discovery group
. You will be responsible for:

• Establishing Prellis’s yeast / phage display platform as the backbone of our antibody optimization engine, owning the scientific strategy, and standing up end-to-end workflows.
• Leading and executing display-based optimization and engineering campaigns
  , including library design, affinity maturation, and property improvement.
• Applying computational engineering to design and engineer antibodies using structural, generative, and sequence-function models; partnering with Data Science / AI/ML to generate training data and close the design-build-test-learn (DBTL) loop.

This role sits within a highly cross-functional High Throughput Discovery group
, working closely with NGS / Bioinformatics, Protein Sciences, and Data Science / AI/ML. The ideal candidate will thrive in a dynamic, hands‑on environment and play a critical role in delivering life‑changing therapeutics.

Responsibilities

Lead antibody optimization and engineering with a strong emphasis on affinity maturation and liability engineering to refine and advance lead candidates toward development. Core activities:

• Build out the yeast/phage display platforms across scFv, Fab, IgG, and VHH formats: strains, vectors, induction and labeling protocols, FACS sorting, and QC.
• Lead biopanning campaigns for affinity maturation and property improvement; design focused and diversified libraries (alanine scanning, site-saturation, CDR-focused, oligo-pool); apply DMS, TITE-Seq, and NGS-based enrichment to drive sequence-function understanding.
• Partner with the computational liability team on develop ability polishing: design experimental approaches and focused libraries to remove sequence / chemical liabilities, mitigate aggregation and immunogenicity, and humanize when needed.
• Drive computational design with Data Science / AI/ML: apply structural tools (PyMOL, Schrödinger, Alpha Fold / Alpha Fold-Multimer) and PLM / generative models (ESM, AbMAP, RF diffusion, RF Antibody, ProteinMPNN); generate ML training data and move manual workflows to automation.
• Manage CRO / CDMO partnerships for biologics production, library construction, and characterization.

Qualifications

• Ph.D. in Biochemistry, Bioengineering, Molecular Biology, Protein Engineering, or related field:
  Senior Scientist (PhD + 3-5 yrs);
  Principal Scientist (PhD + 5+ yrs).
• Proven track record optimizing antibody leads: affinity maturation and liability engineering (sequence / chemical liability removal, aggregation and immunogenicity mitigation, humanization).
• Hands-on with yeast and / or phage display across multiple formats (scFv, Fab, IgG, VHH); TITE-Seq, DMS, or comparable sequence-function methods.
• Strong molecular cloning, mutagenesis, and library construction (Gibson, SSM, EP-PCR, oligo-pool); NGS library prep and enrichment analysis.
• Hands‑on with high-throughput flow platforms (iQue, MACSQuant, or comparable) and FACS‑based screening cascades.
• Computational fluency:
  PyMOL, Schrödinger (Bio Luminate / Maestro),…