5-7 years of experience in drug discovery programs, particularly in decision-making phases like hit-to-lead and candidate nomination.
Advanced degree in chemistry, cheminformatics, toxicology, or computational chemistry.
Strong background in medicinal chemistry, including structure-activity relationships and lead optimization.
Proficiency in computational chemistry, engineering, biochemistry, and machine learning.
Experience with Python and cheminformatics libraries such as RDKit, as well as data processing tools like SQL and Pandas.
Responsibilities
Build and deploy tools and data systems for predicting drug outcomes.
Manage customer deliverables from data generation to analysis and presentation.
Collaborate with pharma drug hunters and researchers to create experimental datasets.
Integrate customer goals into Axiom's workflows and ensure feedback loops are effective.
Enhance Axiom's data quality through independent analyses and scalable frameworks.
Facilitate the use of Axiom's systems in real drug discovery workflows.
Drive insights from customer engagements to improve future analyses.
Benefits
Opportunity to work with leading pharma companies and AI labs.
Collaborative environment with multidisciplinary teams.
Chance to influence the future of drug discovery.
Access to cutting-edge tools and technologies in drug development.
Full Job Description
Key Responsibilities:
Build and ship agentic tools and data systems that let agents accurately predict human drug outcomes
Own key customer deliverables end to end, including data generation, QC/QA, computational analysis, agentic workflows, data presentation, and partnership with sponsors to translate results into drug program decisions.
Partner directly with drug hunters at top pharma companies, researchers at leading AI labs, and Axiom's multidisciplinary team to build the experimental datasets and agentic systems needed to accurately predict human outcomes, then deploy those systems into real discovery workflows to inform major go/no-go decisions across high-value drug programs.
Work closely across Axiom's chemistry, biology, machine learning, engineering, and lab teams to embed each customer's goals and context into our work, and own the feedback loop from customer needs back into Axiom's data generation, models, and agentic workflows.
Ensure Axiom learns from every customer engagement by expanding and productionizing the insights generated by our agentic workflows, while reducing analysis cycle time for each subsequent customer.
Conduct independent analyses of Axiom's data to improve underlying data quality and develop new analytical frameworks that can be scaled through agentic workflows.
Enable leading pharma drug hunters to define the future of drug discovery using Axiom's agents, data, and experimental platform.
Expertise which sparks our interest:
Demonstrated experience with drug discovery programs, especially decision-making in hit-to-lead, lead-op, or candidate nomination.
Medicinal chemistry reasoning around structure-activity and structure-property relationships, matched molecular pairs, and hit-to-lead / lead-optimization design.
ADME/DMPK and PK/PD interpretation, physicochemical property optimization, and exposure-response reasoning.
Strong computational chemistry, engineering, biochemistry, and ML ability.
Presentation (e.g. slides, reports) and soft skills, with the ability to own customer relationships and partnerships with both biotech companies and big pharma.
Key criteria:
Comfortable in both customer-facing and technical roles - you can identify a customer's technical needs, translate them into an Axiom experimental and analytical plan, then guide the execution and communication of results.
Likely an advanced degree in chemistry, cheminformatics, toxicology, or computational chemistry. With significant experience in drug discovery and a proven track record of advancing programs towards development
Comfortable with Python, cheminformatics libraries like RDKit, scientific computing libraries like NumPy, and data processing such as SQL and Pandas.
