Protein Design Scientist
Core
An AI-first scientist leveraging protein language models and generative design to explore sequence-function relationships and pioneer next-generation agricultural traits.
Role type
Applied ML Scientist (Protein Design)
Builds
Next-generation agricultural traits and variant libraries for the trait pipeline
Domain
Agricultural biotechnology / Computational protein design
Deliverable
production ML models
Required skills
Protein sequence/structure modeling, Machine learning model development, Deep learning engineering, Python, Variant library generation, Protein property prediction, Active learning, Bayesian optimization
Preferred skills
Structural integration (AlphaFold, Boltz, ProteinMPNN), Wet-lab workflows, Cloud environments (AWS, HPC), Containerized workflows (Docker, Nextflow), Agricultural biotechnology experience
Technologies
PyTorch, JAX, AlphaFold, Boltz, ProteinMPNN, GNNs, Foldseek 3Di, Rosetta, Docker, Singularity, Nextflow, AWS
Responsibilities
Formulate biological hypotheses and design computational workflows for large scale variant design, Implement and tune state-of-the-art biomolecular ML models, Partner with wet-lab teams to design variant libraries and integrate experimental data, Communicate complex deep learning concepts to stakeholders, Monitor protein design literature for new tools
Seniority
Senior, hands-on IC