ML Scientist I/II, AI for Protein Engineering
Core
Develop and apply generative and predictive ML models to move biomolecule design from in silico hypothesis to wet-lab validated leads.
Role type
ML Scientist (AI for Protein Engineering)
Builds
ML workflows for protein engineering campaigns, de novo generation, sequence/structure property prediction, candidate selection, and active learning.
Domain
Life Sciences / Protein Engineering / Therapeutic Design
Deliverable
production ML models
Required skills
Machine learning fundamentals, protein design, biologics engineering, biological sequence/structure/function analysis, model evaluation planning, collaboration with experimental scientists
Preferred skills
Antibody/nanobody/enzyme/peptide design, structure prediction, diffusion models, flow matching, protein language models, structural biology, conformational dynamics, affinity maturation, design-test-learn loops with wet-lab teams, industry translation of ML research, publications in AI for science
Technologies
Diffusion models, flow matching, protein language models
Responsibilities
Build ML workflows for protein engineering campaigns; Develop methods for de novo generation and property prediction; Integrate protein design methods into software systems; Translate biological objectives into computational problems; Partner with scientists to interpret design outcomes and improve models; Build evaluation frameworks for model generalization
Seniority
Mid-level IC (I/II)