Radical Numerics is an AI research lab building general biological intelligence. Our mission is to master the code of life, and our purpose is to reduce human suffering.
Our team created Evo, and started the field of generative genomics. Our work was featured on the cover of Science, and presented by our CEO on the main stage of TED2025. Evo was used to create the first AI gene therapy tool CRISPR-Cas9, and the first AI whole genome from scratch. Evo 2, featured in Nature, is the largest fully open source AI project across any domain.
Radical Numerics is bringing the rigor of distributed systems, model architecture, and numerics research to the challenges of biology. We’ve redesigned the foundation model training stack to turn the world’s raw scientific data (e.g. biological sequences, experiments, and physical processes), into intelligible, generative models that can expand and accelerate what humanity can understand, design, and cure.
The same generative breakthroughs that enable life-saving cures also lowers the barrier to creating engineered threats and AI-generated bioweapons. We believe these forces are inseparable. Radical Numerics was founded to develop both the power to design and the responsibility to defend.
About the RoleAs Technical Writer at Radical Numerics, you will be the person who makes our science legible — to researchers, to government partners, to the public, and to each other. You will work directly with scientists and engineers building frontier biological AI systems and translate that work into documentation, publications, blog posts, policy briefs, and technical narratives that are clear, precise, and consequential.
Our researchers and engineers have important things to say but limited time to write. You will draw out their ideas through conversation, learn their voice, and shape their thinking into content that lands — whether that's a perspective piece on biosecurity, a blog post about a new model release, or a technical explainer for a government partner. You should be excited to move fluidly between deep technical content and external-facing communication: understanding model behavior well enough to write about it accurately, and understanding your audience well enough to make it matter.
Translate complex work in genomics, biosecurity, and biological AI into narratives that hold up across audiences — researchers, developers, policymakers, and the broader public — without losing what makes the science interesting.
Support external communications including model release documentation, research summaries, policy briefs, and partner-facing materials where technical accuracy is mission-critical.
Collaborate with scientists and engineers on conference presentations and manuscripts, helping them communicate findings in ways that are precise, accessible, and compelling.
Help define how Radical Numerics communicates its capabilities, risks, and mitigations to government agencies, national labs, and global health organizations — audiences for whom clarity and credibility are everything.
Build and maintain internal documentation infrastructure: style guides, knowledge bases, and communication standards that help the team stay coherent as it grows.
A track record of strong technical or scientific writing — in industry, academia, a research institution, or a policy organization. We care about the quality of the work more than where it was done.
The ability to make hard things clear without making them wrong. You understand the difference between simplifying for accessibility and oversimplifying into inaccuracy — and you know which one is appropriate when.
Sound judgment about how to communicate high-stakes, sensitive, or ambiguous technical topics — including AI capabilities, biosecurity risks, and model limitations — accurately and responsibly.
Comfort working inside a fast-moving research environment where the science is still being figured out, the priorities shift, and the ability to ask good questions matters as much as the ability to write good sentences.
A background in biology, computational science, biosecurity, or a related technical field — or demonstrated ability to write fluently about these areas without one.
Experience writing for government, policy, or national security audiences, where precision and credibility carry particular weight.
Familiarity with biological AI systems such as Evo, ESM, AlphaFold, or genomic foundation models.
Published science writing, open-source documentation contributions, or other public work we can read.
Existing relationships in biosecurity, global health, or science policy communities.
Biology is going to be the most consequential application of AI. We're building the systems that will define what that looks like — for medicine, for biosecurity, and for how humanity understands and shapes life itself.
This role puts you inside that work. Not summarizing it from a distance, but embedded with the people doing it — close enough to understand it, skilled enough to make others understand it too. If you're the kind of person who thinks clearly, writes carefully, and finds frontier science genuinely exciting, we'd like to talk.
Radical Numerics is committed to equal employment opportunity and does not discriminate in any employment opportunities or practices based on an individual's race, color, creed, gender (including gender identity and gender expression), religion (all aspects of religious beliefs, observance or practice, including religious dress or grooming practices), marital status, registered domestic partner status, age, national origin or ancestry (including language use restrictions and possession of a driver’s license issued under California Vehicle Code section 12801.9), natural hair, physical or mental disability, political affiliation, medical condition (including cancer or a record or history of cancer, and genetic characteristics), sex (including pregnancy, childbirth, breastfeeding or related medical condition), genetic information, sexual orientation, military and veteran status or any other consideration made unlawful by federal, state, or local laws. It also prohibits unlawful discrimination based on the perception that anyone has any of those characteristics, or is associated with a person who has or is perceived as having any of those characteristics.
Radical Numerics participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
Skills Required
- Track record of strong technical or scientific writing in industry, academia, research institutions, or policy organizations
- Ability to simplify complex technical content without introducing inaccuracies
- Sound judgment communicating high-stakes, sensitive, or ambiguous technical topics (AI capabilities, biosecurity risks, model limitations)
- Comfort working in a fast-moving research environment and collaborating directly with scientists and engineers
- Background in biology, computational science, biosecurity, or related technical field
- Experience writing for government, policy, or national security audiences
- Familiarity with biological AI systems such as Evo, ESM, AlphaFold, or genomic foundation models
- Published science writing, open-source documentation contributions, or other public work
- Existing relationships in biosecurity, global health, or science policy communities
What We Do
The architectures that power modern AI were designed for language, not for science. They were never built to understand DNA, interpret experiments, or learn the rules that govern living systems. Closing this gap represents one of the defining opportunities of our time. Our team has pioneered advances across frontier AI, including the first models trained with one-million-token context windows, and now scaling toward one billion. We focus on innovations on systems and architecture, because building AI for science demands a fundamentally different foundation. As a first application of this technology engine, we are advancing AI for life, the most complex and consequential domain of all. We are the AI team behind Evo and Evo 2, the generative genomics models used to create real gene-editing tools and the first whole genomes designed entirely by AI. That work demonstrated that AI can create biology, not just analyze it. We are now building multimodal models trained directly on the fabric of biology, enabling faster discovery, deeper understanding, and entirely new capabilities. As we push the frontier of general biological intelligence, we will build systems hand-in-hand to ensure global biological resilience: rapid detection, rapid response, and rapid countermeasures against emerging threats, both natural and synthetic. Our mission is ambitious: to reimagine what AI can do for biology, and to build that future. Our advisors include Eric Horvitz, CSO of Microsoft, Chris Ré of Stanford, George Church of Harvard, and Andrew Weber, former Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense Programs.
Why Work With Us
We bring the rigor of distributed systems, model architecture, and numerics research to the hard problems of scaling learning on biological data. If this resonates, we'd love to hear from you.
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