СШАResearch Scientist, Applied Research
4 дн. назад
СШАSeniorOnsite
machine learningdata analysismodel evaluation
Research Scientist role focused on improving foundation models for drug discovery by planning data campaigns, designing evaluations, and formulating post-training methods.
О компании
- Chai Discovery builds the computer-aided design suite for molecules. Eli Lilly , GSK , Pfizer , Bristol Myers Squibb , argenx and Novartis all use Chai to power drug discovery programs. AI is reinventing life sciences the same way it reinvented software engineering, and our team is building that future.
- We train frontier models that learn the underlying foundations of biochemical structure and interaction. We pair this with a computational workspace to iterate on molecules from idea to medicine, helping scientists move faster and develop medicines beyond the reach of existing methods.
- We value diverse perspectives and are ready to find greatness in unexpected places.
Обязанности
- We are hiring research scientists to improve the real-world performance of our foundation models. The work involves planning targeted data generation campaigns, designing evals that accurately measure model performance, and formulating post-training recipes aimed at making models useful for real drug discovery problems.
- We prioritize simple, robust methods over intricate solutions built for narrow problems. We particularly value researchers who can formalize messy biological problems using methods from other fields.
- You will work in tight loops with our pre-training researchers, research engineers and science team. Your work will ship fast and you'll see your results reach real therapeutic programs across industry.
Требования
- We look for technical depth paired with interest in the underlying biology. Biological background is not required. All of the following are positive signals:
- Published research in machine learning for protein, antibody, or small-molecule modelling.
- Fluency in the technical details of protein language, structure prediction, and design models (AlphaFold, RFDiffusion, ProteinMPNN, ESM, etc).
- Strong quantitative background (CS, math, or physics), particularly in probability, statistics, and machine learning.
- Deep software engineering expertise, with experience working in large codebases.
- We are happy to bet on rising talent.
Условия
- The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters. We protect and promote a culture of high velocity and ownership. We compensate our team accordingly.