Senior Medicinal Chemist

Axiom Bio; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Axiom is seeking exceptional drug discovery scientists with strong computational and mathematical instincts to help build our ecosystem. You will work directly with scientists at top pharma/biotech, researchers from leading AI labs, and Axiom’s multidisciplinary team to build experimental datasets, agentic systems, and product capabilities needed to predict human drug outcomes.

They will deploy these agents into real discovery workflows to inform go/no-go decisions on high-value programs.

Qualifications

• Experience in drug discovery programs and decision-making in hit-to-lead, lead-op, or nomination.
• Strong background in medicinal chemistry, SAR/SPR, and lead optimization design.
• Expertise in ADME/DMPK, PK/PD interpretation, and exposure–response reasoning.
• Proficiency in computational chemistry, engineering, biochemistry, and ML.
• Ability to own customer relationships and partnerships with biotech and pharma.

Responsibilities

• Build and ship agentic tools and data systems to predict human drug outcomes.
• Own customer deliverables end-to-end: data generation, QC/QA, analysis, workflows, data presentation, and sponsor collaboration.
• Collaborate with sponsors, pharma researchers, AI labs, and internal teams to deploy agentic systems into discovery workflows.
• Embed customer goals with chemistry, biology, ML, engineering and lab teams; feed back customer needs into data generation and models.
• Expand and productionize insights from workflows; reduce analysis cycle time for subsequent customers.
• Perform independent analyses of data to improve quality and develop scalable analytical frameworks.
• Enable pharma drug hunters to define the future of drug discovery using agents, data, and experimental platform.

Skills

Python

RDKit

NumPy

Pandas

SQL

Education

Advanced degree in chemistry/cheminformatics/toxicology/computational chemistry

Tools

RDKit

Job description

Axiom is building the closed-loop scientific AI system required to replace animal testing and, over time, much of human safety testing. We start with pharma’s hardest drug development toxicology problems. Those problems define the proprietary human biological data we generate through Axiom’s Data Factory. We use that data to train scientific AI, partnering with leading AI labs to improve frontier models while building our own specialist agentic harness to deploy the improved frontier models back into pharma. Each deployment reveals the next capabilities to build, creating a compounding loop across data, models, and drug development. Today, liver toxicity is our proving ground. Axiom is already helping leading pharmaceutical companies understand toxicity, identify its mechanism, and design safer drugs. Over time, we will expand across the major organ systems and build the experimental and agentic system of record for translational drug development. Our goal is to dramatically reduce the risk of testing new molecules in humans, enabling high throughput evaluation of efficacy in humans.

Who we are looking for:

We are looking for exceptional drug discovery scientists who also have strong computational and mathematical instincts to help build and grow Axiom’s ecosystem. In this role, they will work directly with great scientists at top pharma and biotech companies, researchers from leading AI labs, and Axiom’s multidisciplinary team to build the experimental datasets, agentic systems, and product capabilities needed to accurately predict human drug outcomes. They will also partner closely with scientists inside leading pharma companies to deploy these agents into real discovery workflows, where they will be critical for informing major go/no-go decisions across many high-value drug programs. We want to hire people who inspire us and level up the entire team. They should be high energy, high agency, and have great taste for what matters. They should have a relentless “observe, orient, decide, act” loop, and be constantly identifying what needs to happen and getting it done. They need to be technically excellent and obsessive masters of their craft, as well as having a great curiosity which will keep them at the frontier of tech and help them interface between AI, engineering, product, biology, chemistry, and business. They could work in big tech or pharma, but it won’t satisfy them. They want to go on an adventure which will be brutally challenging, and to share in the rewards and satisfaction at its end.

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.