Machine Learning Scientist Pretraining
AI-first protein-design company using generative foundation models and wet-lab validation to create functional proteins and genome-editing systems.
Funding history
About Profluent
Profluent develops AI models for de novo protein design, with applications in biomedicine, agriculture, and industrial biology. Its platform includes protein-generation models such as ProGen3 and the AI-designed OpenCRISPR-1 gene editor.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will research, prototype, evaluate, and improve large-scale deep learning models for biomolecular and protein design. You will build pretraining infrastructure, curate evaluation datasets, analyze computational approaches, present findings, and collaborate across machine learning and protein design disciplines.
Requirements
- PhD or equivalent industry experience in a relevant technical or scientific field
- Experience conceiving, implementing, and evaluating novel machine learning and pretraining large-scale models in the biomolecular domain
- Publications at major machine learning conferences or scientific journals, or experience pretraining LLMs at frontier AI/ML labs
- Experience with PyTorch or JAX
- Legal authorization to work in the United States
Responsibilities
- Design and develop autoregressive, diffusion, and representation-learning models for protein design
- Adapt and improve pretraining techniques for biomolecular deep learning models
- Architect, implement, and optimize infrastructure for pretraining protein language models
- Curate datasets and design evaluation tasks for generative models
- Implement, analyze, interpret, and present computational approaches
Benefits
- Equity participation
- 401(k) with employer match
- Health, dental, and vision insurance
- Generous PTO policy