---
title: 'Platform Engineer at Axiom'
canonical: 'https://feeny.ai/job/platform-engineer-axiom-san-francisco-ampbtde2smms'
type: 'job'
last_seen: '2026-09-13'
---

# Platform Engineer at Axiom

- **Company:** Axiom
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Posted:** 2026-07-17
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/axiombio/934dbea4-2bd7-4e6f-927e-a75636a0d052

## Job description

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. What you will be doing:

- Lead Axiom’s evolution into a world-class engineering company focused on enterprise ML software
- Design and build the core infrastructure that powers Axiom’s enterprise ML systems, including model evaluation/deployment, model inference/serving, and customer data management
- Architect scalable systems for inference, storage, and retrieval of chemical, biological, and clinical data
- Deploy large-scale reasoning agents from research environments into production, integrating them into on-prem customer-facing products and infrastructure
- Teach and empower scientists across ML, chemistry, and biology to become great engineers by instilling a great engineering culture

Various expertise which gets us interested:

- Built SaaS products that store and process large volumes of customer data.
- Worked directly with large enterprise customers and supported their complex software needs
- Designed and developed large-scale machine learning systems covering data access, training, evaluation, and deployment
- Handled the “messy” parts of ML deployment, such as evaluation pipelines, versioning, and monitoring
- Built LLM-powered data systems, with a focus on research workflows and information retrieval

Key criteria:

- Strong generalist software engineer with experience across cloud infrastructure,machine learning, backend systems, distributed systems
- Enjoys working with enterprise customers and simplifying complex technical solutions to meet their needs
- Built and deployed production systems used by large enterprise businesses
- Invested in team growth particularly when it comes to building strong engineering culture across the company
- Passionate about collaborating with researchers and scientists, helping them become strong engineers
- Takes full ownership of the customer experience—deeply focused on reliability and all the ways things can go wrong
- Demonstrates relentless

## 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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