Research Scientist Applied Research
AI molecular-design company building models and a computer-aided design suite for drug discovery.
Funding history
About Chai Discovery
Chai Discovery develops generative AI software that predicts and reprograms biochemical molecular interactions to help scientists design biomolecules and medicines.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will improve the real-world performance of foundation models for drug discovery. You will plan targeted data-generation campaigns, design evaluations that measure model performance, and formulate post-training recipes for real drug-discovery problems. You will work closely with pre-training researchers, research engineers, and scientists, iterating quickly so your results reach therapeutic programs.
Requirements
- Published research in machine learning for protein, antibody, or small-molecule modelling
- Fluency in protein language, structure prediction, and design models
- Quantitative background in computer science, mathematics, or physics
- Knowledge of probability, statistics, and machine learning
- Software engineering expertise and experience with large codebases
Responsibilities
- Plan targeted data-generation campaigns
- Design evaluations that accurately measure model performance
- Formulate post-training recipes for real drug-discovery problems
- Collaborate with pre-training researchers, research engineers, and the science team