Senior / Principal Scientist, AI for Protein Engineering
About the role
The Senior or Principal Scientist will develop and execute protein design and engineering workflows for antibody campaigns, including de novo design, affinity maturation, and developability optimization. They will translate campaign requirements into well-defined ML problems and design specifications, and adapt and extend state-of-the-art AI methods to the specific demands of antibody and broader biomolecule engineering. This role requires a PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, or a related field, with proven track record in AI for protein engineering.
Responsibilities
- Develop and own protein design and engineering workflows for antibody campaigns, including de novo design, affinity maturation, and developability optimization
- Execute design workflows end-to-end for active campaigns and deliver wet-lab-validated leads against program milestones
- Translate campaign requirements — epitope selection, affinity targets, biophysical constraints, and developability criteria — into well-defined ML problems and design specifications
- Adapt and extend state-of-the-art AI methods (generative models, protein language models, structure-conditioned design) to the specific demands of antibody and broader biomolecule engineering
- Partner with the Life Science Research team on design validation, building active learning loops where wet-lab data refines and improves model performance
- Expand the protein engineering platform to additional modalities such as enzymes and peptides as needs evolve
Requirements
- PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, or a related quantitative field
- Proven track record of successful design of wet-lab-validated biomolecules through AI, with industry experience strongly preferred
- Deep ML expertise with the ability to modify and adapt state-of-the-art AI approaches for protein engineering, not just apply them off-the-shelf
- Strong fluency across both ML and protein biology, with hands-on understanding of antibody design
- Demonstrated ability to drive a research and engineering program independently, from problem definition through experimental validation and iteration
- Clear communication across the ML/biology boundary
Qualifications
- Track record of close collaboration with experimental scientists
- Bonus points for direct experience designing antibodies, nanobodies, or other therapeutic proteins for clinical or therapeutic pipelines
- Experience with structure prediction, generative protein design (diffusion, flow-matching, or similar), and protein language models in a production research setting
- Experience in structural biology and conformational dynamics
- Experience extending design methods to additional modalities such as enzymes, peptides, or other engineered biomolecules
- High-impact publications or open-source contributions in AI for Science (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent)
Skills
- Strong fluency across both ML and protein biology
- Hands-on understanding of antibody design
- Ability to adapt and extend state-of-the-art AI methods for protein engineering
- Experience with structure prediction, generative protein design, and protein language models
- Experience in structural biology and conformational dynamics
- Experience extending design methods to additional modalities such as enzymes, peptides, or other engineered biomolecules
Benefits
Compensation: Competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits: Medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company-wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office-based employees; and a company-subsidized lunch program.
International Benefits: Comprehensive benefits program tailored to your region.