Chai Discovery is re-architecting drug discovery by building frontier AI foundation models to design molecules.
The founding Chai team has brought together the leading researchers in this space, with seminal research accomplishments at top AI labs. The team has led AI-for-biology programs at premier labs, co-invented protein language modelling, built state-of-the-art folding algorithms, and sold AI adopted by top-10 pharma companies. The company is backed by top-tier investors, including OpenAI, Thrive Capital, Dimension, Conviction, Lachy Groom, Amplify, and many more.
We’re looking to add a few members to our team of scientists and engineers, who obsess over creating the most powerful AI models for antibody discovery, and turning them into products that can transform how medicines are made.
We’re hiring an exceptional and versatile Computational Scientist (Biologics) to play a critical role in therapeutic design benchmarking at Chai. You won’t just focus on a single target — you’ll work across dozens of the most compelling problems in biotech, helping to unveil new possibilities in drug design.
At Chai, we’re entering a pivotal stage. After years of foundational R&D, our models are moving beyond protein structure prediction and into real-world therapeutic engineering. We're now tasking our AI models on a broad spectrum of drug development challenges, at an exciting scale of wet-lab validation.
This is not a typical role — it’s a chance to push the boundaries of drug discovery by building some of the most advanced AI drug design models ever built.
We are seeking a biologist with rigorous therapeutic research, with a deep desire to push the limits of what’s possible in therapeutic design and a restless drive to solve real-world problems and iterate quickly.
You should have:
Significant scientific experience:
A strong command of molecular biology, protein science, or a related discipline
5+ years of experience in biotech or biomedical research (antibody discovery or related areas preferred)
Fluency in applied computational biology:
Comfort writing and debugging code (Python preferred) — you won’t need to build AI models in this role, but you will be using them on a daily basis
Writing Python scripts for data analysis (e.g. ingest diverse data types, compute basic statistics like correlation or enrichment, create quantitative plots)
Interpreting protein structures in PyMol, analyzing sequence alignments, and producing clear illustrations to support scientific conclusions
Ability to lead lab projects, including:
Defining the experimental efforts required to reach high-level goals (e.g. elucidate a drug’s biochemistry, MoA, or specificity)
Interrogating and refining lab results with sufficient rigor for a TPP and/or peer-reviewed publication
You have fun solving problems that others think are impossible
Comfort with ambiguity and rapid context-switching
Relevant hands-on experience (any subset is valuable):
Protein production and purification
Affinity measurements (BLI, SPR, ELISA)
Antibody polyreactivity characterization
Antibody solubility and developability assessments (aggregation, viscosity)
Cell-based functional assays (e.g. receptor signaling, cytokine release, FACS)
In vivo modeling (PK/PD, efficacy, toxicity)
3D structure determination and analysis
Phage and/or yeast display
Rational mutagenesis of antibodies
Procuring reagents and coordinating contract research work
Frontier technology: we’re developing the next frontier of AI-driven drug discovery that will fundamentally change how new therapeutics are created.
World-class team: opportunity to work with world-renowned leaders in the AI x biology and technology ecosystem who have created some of the most impactful advancements.
Highly competitive compensation: we offer highly competitive salary, equity package, and healthcare and wellness benefits.
Velocity and ownership: we move incredibly fast, which means continuous learning and career growth opportunities are a guarantee. Every team member owns a significant slice of the roadmap.
Strong team culture: Collaborative and supportive startup culture in a small and high-energy team who are guided by our mission to increase the efficiency of creating new medicines and positively impact millions of lives.
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