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
Own operational delivery of Axiom’s scientific data programs, translating research and customer requirements into clear plans, milestones, quality standards, budgets, and deliverables. Coordinate data generation across internal teams and partner laboratories, managing capacity, dependencies, timelines, and handoffs from experimental planning through validated data delivery. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Data management and analysis using spreadsheets, SQL, Python, dashboards, and automated reconciliation and validation tools
- Program planning, dependency tracking, capacity planning, risk management, and quantitative process improvement
- Workflow automation and AI agents for tracking deliverables, reconciling records, coordinating handoffs, and surfacing exceptions
- Vendor and commercial operations, including SOWs, purchase orders, invoices, budgets, and performance tracking
- Compound procurement, supplier coordination, inventory management, international shipping, and customs documentation
- Scientific operations, including experiment scheduling, sample tracking, compound identity management, and laboratory data delivery
More about this role
Own the operations that turn Axiom’s scientific plans into massive, high-quality experimental datasets that power frontier agents and models to predict human drug outcomes with insane accuracy.
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 reinforcement learning environments that train increasingly superhuman scientists. We then deploy these frontier models to...
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