Chai DiscoveryResearch Scientist, Applied Research
Chai Discovery is hiring a Research Scientist, Applied Research in San Francisco, United States. Level rates it ; you can apply on Chai Discovery.
Level's read on this job
- On Level's scale, this research scientist role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions Alphafold, Rfdiffusion and Proteinmpnn among its tools and skills.
- Chai Discovery has 20 other open roles on Level.
- Posted in the last few days.
AI in this role
Improve foundation model performance for drug discovery through targeted data generation, evals, and post-training recipes.
About Chai Discovery
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.
About the role
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.
About you
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.
We offer
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.
How we rate this
Research Scientist, Applied Research at Chai Discovery rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in research scientist jobs at this level
Pay
- Typical research scientist job
- $192k
This posting doesn't list pay. Use the typical research scientist figure when pay comes up. See research scientist jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where protein modeling was part of your work. What did you do?
- Tell me about a project where antibody modeling was part of your work. What did you do?
- Tell me about a project where evaluation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Machine learning, Protein Modeling, Antibody Modeling, and Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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