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 RoleYou own the diagnostics side of our business. You identify where in clinical genomics companies, laboratories, and health systems our deals get funded, including product, R&D, and the laboratory itself.
Our science team owns the model itself. You decide what we build on top of it so a clinical organization can run our scoring inside a test they have already validated. The people who evaluate us are bioinformatics teams and lab directors, and they don't move without validation on their own data, so you will have a lot of say in which studies we run.
You should be comfortable building prototypes. You are paired with an applications engineer who builds production product, and you go into partner meetings together.
You will carry a commercial target, weighted early toward getting a partner into production.
Decide which interpretation problems we solve and for whom, and what has to be true technically before a clinical organization will run our output in production.
Originate and close partnerships with clinical genomics companies, laboratories, and health systems. You are measured on committed contract value and on partners running our scoring in production rather than in pilots.
Design the studies that convert a clinical buyer. Blind retrospectives on solved cases, concordance against the tools they use today, and reclassification yield on their own backlog.
Tell our engineering team what production use requires from us, including version pinning, provenance, and the documentation a partner's quality system needs.
Flag early when an opportunity needs us to build something we do not have.
Set pricing and structure with the Head of Product, and run the negotiation with our legal team.
Depth in clinical variant interpretation. ACMG and AMP criteria, ClinVar and its limits, VUS reclassification, and what a lab director or genetic counselor needs from a call.
You have sold into clinical laboratories or diagnostics companies and carried a number.
Working fluency in CLIA, CAP, the laboratory developed test landscape, and what analytical validation asks of a software component inside an assay.
You stay useful when the real objection is reimbursement, liability, or the buyer's own validation burden rather than the science.
You want to own revenue, and you can run a long clinical sales cycle without going quiet inside it.
Nice to Have
You have worked inside a clinical laboratory or a diagnostics company.
Experience across both germline and somatic interpretation.
You understand how a new component inside an existing billable test gets funded.
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
- Depth in clinical variant interpretation (ACMG and AMP criteria, ClinVar, VUS reclassification)
- Proven sales experience selling into clinical laboratories or diagnostics companies and carried revenue targets
- Working fluency in CLIA, CAP, and laboratory developed test landscape, including analytical validation expectations for software components
- Comfort building prototypes and working with applications/engineering teams to translate prototypes to production requirements
- Ability to design and run validation studies (blind retrospectives, concordance, reclassification yield) to convince clinical buyers
- Experience negotiating pricing and contract structure with legal involvement and owning long clinical sales cycles
- Ability to engage with lab directors, genetic counselors, and bioinformatics teams and address non-technical objections (reimbursement, liability, validation burden)
- Experience working inside a clinical laboratory or diagnostics company
- Experience across both germline and somatic variant interpretation
- Understanding of how a new component inside an existing billable test gets funded
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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