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 roleWe are hiring research scientists with outlier insight who can open new avenues for the work we pursue. Our models have moved beyond protein structure prediction into real-world therapeutic engineering, and we have only just begun. We draw on the best ideas from within our domain and from across the field: pre-training large diffusion models, architecture design, post-training, and inference-time scaling.
Our team comes from physics, math, theoretical computer science, engineering, and computational biology. What we share is a record of getting hard, open-ended problems to work, and together we foster a culture of rigor, smart risk-taking, and constant collaboration. Many of us had never worked on molecules or biology before Chai.
This is the place to apply if your strongest work happened outside AI for biology, or if you aren't sure which of our research roles fits you best.
About youWe are looking for researchers driven by impact. We index on grit, rigor and results.
A research record of your own, in academia or industry: first-author work, a method others adopted, or a system you got working at scale in the real world.
Strong reasoning from first principles and sound experimental design, and you're comfortable with ambiguity and messy data.
Enough engineering to be self-sufficient: you implement your own models and run your own experiments.
We value the work product more than the pedigree, and we are happy bet on rising talent. A strong signal in any field counts, from world models or autonomous systems to top placement at IMO or Putnam.
We offerThe 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.
Skills Required
- Ph.D. or equivalent research experience in Machine Learning, Computational Biology, Bioinformatics, Computational Chemistry, or related field
- Strong publication or project record in top ML or life-science venues (e.g., NeurIPS, ICML, Nature Methods)
- Proficiency in Python and deep-learning frameworks
- Experience training and evaluating large models on protein, antibody, or small-molecule data, or demonstrably transferable ML expertise
- Ability to translate open-ended scientific questions into tractable modeling experiments
- Skilled at wrangling large biological or chemical datasets, computing meaningful metrics, and visualizing results
- Strong collaboration and communication skills for cross-functional teams and non-technical stakeholders
What We Do
Building frontier artificial intelligence to predict and reprogram the interactions between biochemical molecules.
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