---
title: 'Senior Drug Discovery Scientist at Axiom'
canonical: 'https://feeny.ai/job/senior-drug-discovery-scientist-axiom-san-francisco-djnwasb78tjn'
type: 'job'
last_seen: '2026-09-13'
---

# Senior Drug Discovery Scientist at Axiom

- **Company:** Axiom
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-09
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/axiombio/c53d8fd6-7ed9-4e58-9274-66605d677721

## Job description

Charter: Join Axiom as a founding team member and help build a technology ecosystem that will replace animal testing and ultimately reshape clinical trials through agentic systems that can accurately predict human outcomes.

About Axiom: Axiom is building an ecosystem to compound technology which will replace animal testing and, over time, reshape how clinical trials are run. We partner with leading organizations to transform capital into proprietary data and machine learning models, then deploy those models across the world’s largest pharmaceutical companies to improve how medicines are discovered and developed. It starts with deeply understanding the needs of drug hunters inside large pharma, especially around drug toxicity and safety. Those needs shape the world-class datasets we build from scratch. We then use that data to advance our own ML research, while also collaborating with leading AI labs to improve frontier models’ ability to reason over Axiom’s data inside Axiom’s agent harness. This creates a compounding loop: deeper customer understanding shapes the data we generate; better data improves frontier models, Axiom’s fine-tuned models, and our agentic infrastructure; stronger models and tooling expand the capabilities we can offer; and those capabilities are forward deployed into pharma's drug discovery workflows, where scientists use them to solve the highest value drug discovery problems. In turn, this helps us identify the next problems to tackle. Today, we are focused on solving drug-induced liver injury through an integrated data and agentic system already being used by 7 of the top 20 pharma companies and several of the world’s most innovative biotechs. Over time, Axiom will invest billions into the world’s largest human datasets across all the major organ systems, paired with an agentic harness that uses this data to predict human drug outcomes dramatically better than animals and phase 1 clinical trials.

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.

## About Axiom

## Company Overview
- **One-liner**: Axiom builds an AI platform that predicts human drug toxicity from lab data, helping pharmaceutical companies develop safer medicines with less animal testing.
- **Entity Type**: Private (Seed round, April 2025)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Brandon White, Alex Beatson

## Core Business
- **Primary industry**: Biotechnology Research / Artificial Intelligence for Drug Discovery
- **Target customers**: B2B – pharmaceutical and biotech companies, drug discovery teams
- **Mission or purpose statement**: "Understand drug toxicity before it reaches humans" – using “frontier intelligence” to end unexpected drug toxicity and reduce clinical trial failures.

## Products & Services
- **Toxicity Prediction Platform**: An agentic AI system that connects experimental data (cell painting, mass spectrometry, metabolism assays) to clinical outcomes. Provides mechanistic, exposure-aware risk assessments early in discovery. (SaaS/API platform)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Seed round (April 2025) with participation from at least three investors; total funding amount not disclosed.
- **Notable Investors/Partners**: Amplify Partners, Abstract VC, Dimension Capital, Zetta Venture Partners, CRV; advisors include Jeffrey Dean (Google DeepMind), Yvonne Will (former Pfizer), Nicholas Meanwell (medicinal chemistry leader).
- **Growth Signals**: Headcount grew 108% YoY (22 employees); LinkedIn followers grew 287% YoY; website traffic up 277% YoY; actively hiring for ML, data, and platform engineering roles.

## Competitive Advantages
- **Human-relevant data core**: Models trained on primary human hepatocytes and clinical outcomes rather than animal models, directly addressing the 90% clinical failure rate.
- **Mechanistic AI**: Provides interpretable, exposure-aware risk profiles instead of black-box hazard flags, enabling chemists to modify compounds.
- **World-class advisory board**: Deep expertise from pharma safety, medicinal chemistry, and ML (e.g., Nicholas Meanwell, Yvonne Will, Jeffrey Dean).

## Strategic Focus
- Replace traditional animal-based toxicity tests with AI-driven, human-relevant predictions.
- Expand from liver toxicity (DILI) to other organ systems and broader safety readouts.
- Scale customer integrations via enterprise SaaS and collaborative research partnerships.

## Why Work Here
- **Culture**: Fast-growing startup (founded 2024) with a tight-knit team of ~22, emphasizing both scientific rigor and engineering excellence.
- **Work environment**: Hybrid/remote-friendly (roles listed as “In-Office or Remote”); offices in San Francisco with remote team members in Canada and Israel.
- **Engineering culture**: Strong ML and platform engineering focus; stack includes Python, PyTorch, React, Typescript, and scientific libraries.
- **Open roles** (as of mid-2026): Platform Engineer, Data Engineer, ML Researcher, Product Engineer, Computational Scientist (Mass Spectrometry) – posted on [jobs.ashbyhq.com](https://jobs.ashbyhq.com/axiombio) and [Built In](https://builtin.com/company/axiom-bio/jobs).

## Sources
1. [axi.om/company](https://www.axi.om/company)
2. [linkedin.com/company/axiombio](https://www.linkedin.com/company/axiombio)
3. [axi.om/mission](https://www.axi.om/mission)
4. [builtin.com/company/axiom-bio/jobs](https://builtin.com/company/axiom-bio/jobs)

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