Senior Scientist-Principal Scientist-Antibody Protein 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.

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 develop ability 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.

• 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, mini bodies, Fab, VHH, Fc fusions, albumin fusions, TCRm) and assemble multispecifics (knob‑in‑hole, Cross Mab, 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 & develop ability — 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 Bio Luminate / Maestro) and partner with Data Science / AI/ML on protein language and structure models (Alpha Fold, ESM, RF diffusion, ProteinMPNN, or equivalent)

• Ph.D. in Biochemistry, Bioengineering, Molecular Biology, Protein Engineering, or related field with equivalent industry experience:
  Sr. Scientist (PhD + 3‑5 yrs);
  Principal Scientist (PhD + 5+ yrs)
• Hands‑on biologics reformatting across scFv, scFv‑Fc, Fab, Fc fusions, VHH, and Fc engineering
• Demonstrated experience optimizing / engineering antibody lead candidates (affinity, develop ability, and Fc properties) and hands‑on experience with biologics screening using iQue and MACSQuantor high content imaging (HCI).
• Computational fluency:
  PyMOL, Schrödinger (Bio Luminate / Maestro), molecular dynamics, or equivalent, and at least one protein language model (ESM, RF diffusion, ProteinMPNN, or equivalent)
• Strong molecular cloning, mutagenesis, and DNA library construction
• Mentorship of junior researchers; clear scientific communication; track record of publications, presentations, or patents
• Experience managing external vendors (CROs / CDMOs) for biologics production and characterization
• Thrive in cross‑functional collaboration

• Strong background in antibody discovery pipelines: expression, purification, screening, and analytical characterization.
• Experience continuous directed evolution (Ortho Rep, PACE): high‑diversity libraries (yeast, ribosome, mRNA, mammalian), multi‑round selection, and quantitative affinity binning liquid‑handling automation (Biomek, Lynx, Tecan), LIMS / ELN (Benchling)

At Prellis we integrate human biology with machine learning. We aim to revolutionize drug discovery…