Protein Design Scientist, Machine Learning
Core
Design and optimize computational workflows for large-scale protein variant design and property prediction to accelerate agricultural trait discovery using AI-first approaches.
Role type
Senior Applied ML Scientist (Protein Design)
Builds
Innovative protein design pipelines and variant libraries for agricultural traits
Domain
Agricultural biotechnology / Computational protein design
Deliverable
production ML models
Required skills
Protein sequence-structure-function modeling, Machine learning for protein design, Deep learning engineering, Python, PyTorch or JAX, Active learning, Bayesian optimization
Preferred skills
Structural integration (AlphaFold, Boltz, ProteinMPNN, GNNs), Wet-lab workflow familiarity, Cloud environments (AWS, HPC), Containerized workflows (Docker, Singularity, Nextflow)
Technologies
PyTorch, JAX, AlphaFold, Boltz, ProteinMPNN, GNNs, Rosetta, AWS, Docker, Singularity, Nextflow
Responsibilities
Formulate biological hypotheses and design computational workflows for variant design; Implement and tune state-of-the-art biomolecular ML models; Partner with wet-lab teams to integrate experimental screening data; Communicate complex deep learning concepts to stakeholders; Monitor literature to bring new tools and project ideas to the team
Seniority
Senior, hands-on IC