Computational Scientist (Chemistry)
Axiom Bio - San Francisco, California, United States, 94199
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Computational Scientist (Chemistry)
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Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models Charter:
Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models
About Axiom:
At Axiom, we’re redefining how drug safety is assessed by building the world’s most accurate models for predicting human, clinical toxicity. We're looking for a computational chemist who’s excited to apply deep modeling expertise to real-world impact—helping eliminate animal testing and prevent clinical failures. You’ll work closely with our biology, machine learning, and lab teams to develop novel machine learning algorithms, improve model generalization across chemical space, and guide chemical dataset design. This role is ideal for someone who thrives in a fast-moving environment, wants ownership over major scientific contributions, and is motivated by solving foundational challenges at the intersection of chemistry, AI, and human health.
What are we looking for:
At the highest level, we only want to hire people who deeply inspire us and relentlessly push us to be better. They must level up the entire team, bringing significant energy and a sense of awe. High agency is critical: they see what’s important and they do it. Doing is the key but it should be guided by great taste for what truly matters. We’re looking for folks doing those niche hobbies and activities, the ones that might not make sense at first glance, but eventually reveal profound depth and passion when you dive in with them. These individuals act with intentionality or whimsical naivety like an immigrant in a new country, a performer trying to break out, or someone teaching themselves to code or garden. There must be a deep curiosity for all facets of Axiom, an ambition fueling their exploration of what we do. They want to do something here, to dive in headfirst, but they know they need to learn more, so they search with an insatiable hunger. They need to be cracked, technically excellent, obsessive masters of their craft. They're irrational; they could work in big tech, but they know it will not satisfy them. They want the pain of doing something brutally hard along with the riches and glory when it finally works.
What you will be doing:
Collaborate with machine learning researchers to drive the development of cutting-edge models for molecular property prediction. Clean, curate, and process large-scale chemistry datasets spanning hundreds of thousands of unique compounds. Build intuition for how small molecule structure drives key properties like ADME, toxicity, PK/PD, and cellular biology. Analyze model outputs to pinpoint high-performing and underperforming chemotypes, guiding both scientific insight and model refinement. Partner directly with top drug hunters at Pfizer, Takeda, Gilead, Merck, and others to interpret model predictions and accelerate decision-making. Design new strategies to expand our chemical dataset intelligently—driven by ML performance and real-world usage. Influence active drug programs and play a role in advancing how the world’s leading pharma teams develop safe, effective medicines. Help shape Axiom’s product based on customer feedback and insights you uncover from the field. Operate at the intersection of chemistry, biology, machine learning, and product design—pushing forward a transformative technology platform
Expertise which sparks our interest:
Likely either has an advanced degree in chemistry, cheminformatics, or computational chemistry, or has industry experience at a drug discovery company Might identify as a ML for chemistry researcher, computational chemist, medicinal chemist, or cheminformatics scientist Experience working with drug hunters on real drug programs Presentation (e.g. slides, reports) and soft skills with the ability to own customer relationships and partnerships with both biotech companies and big pharma Coding and statistics background: should be comfortable with python, with cheminformatics libraries like rdkit and datamol, scientific computing libraries like numpy, and ideally also with data processing (SQL, pandas, basic cloud computing). Experience analyzing massive chemical datasets and diving conclusions based on statistics and chemistry
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