Axiom provides frontier intelligence for human drug toxicity, helping scientists reduce unexpected toxicity earlier and develop safer medicines with less animal testing. Backed by Amplify Partners.
About the role
Build production-grade Python and SQL pipelines to ingest, process, validate, and serve high-content imaging, omics, mass spectrometry, and ADME data alongside chemical and clinical datasets. Own the shared data infrastructure that powers Axiom’s experiments, models, and scientific agents, including orchestration, storage, compute, isolated development environments, and continuous integration. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong Python and SQL, scientific computing with NumPy and pandas, and analytical databases such as DuckDB or MotherDuck
- Cloud infrastructure and reproducible compute using tools such as Modal, AWS, Docker, and Terraform
- Data pipeline design, orchestration, schema design, automated validation, versioning, lineage, and observability
- Statistical inference and experimental design, including hypothesis testing, multiple-testing correction, variance decomposition, and hierarchical modeling
- Regression, classification, tree-based models, regularization, and cross-validation that respects experimental groups and batch structure
- Model evaluation, including ROC-AUC, PR-AUC, calibration, precision and recall, leakage prevention, and the limitations of different metrics
More about this role
Build the data systems that turn Axiom’s laboratory, chemistry, and clinical data into reliable foundations for drug discovery and scientific AI. Combine strong engineering with rigorous statistics to catch errors, deliver reproducible datasets, and power the models and agents that predict human drug outcomes.
Axiom’s mission is to eliminate unexpected drug toxicity and unlock an abundance of ultra safe medicines. We are starting with the liver, where toxicity remains a leading cause of drug failure. Our high-throughput human liver safety platform combines advanced human cell systems with imaging, transcriptomics, mass spectrometry, and drug metabolism measurements. Our AI agents integrate these data with chemical structure, human exposure, and thousands of clinical reference compounds to predict whether a drug will be toxic in humans, why, and how to make it safer.
We work with seven of the world’s top twenty pharmaceutical companies to design safety into molecules from the earliest stages. This applied work feeds directly into our partnerships with leading frontier AI labs, turning real discovery challenges and experimental feedback loops into scientific skill trees and...
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