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 the lead of Radical Numerics’ biological data discovery efforts, you will operate at the frontier of science, partnerships, and exploration. Your mission is to identify and unlock the world’s most valuable biological datasets, many of which are not publicly available and require trust, relationships, and persistence to access.
This role is part strategist, part explorer, and part dealmaker. You will work closely with our AI researchers and scientists to identify which datasets will have the greatest impact on training the next generation of biological world models. You will then travel globally to meet researchers, hospital systems, national biobanks, sequencing centers, and pharmaceutical partners face-to-face, building relationships that allow Radical Numerics to access these datasets.
Global data discovery
Map the global landscape of biological datasets across genomics, epigenomics, transcriptomics, proteomics, metabolomics, imaging, and clinical data.
Identify high-value datasets across pharma pipelines, national biobanks, hospital systems, sequencing centers, research institutes, and government repositories.
Relationship building
Travel internationally to build trusted relationships with scientists, hospital administrators, sequencing labs, biotech companies, and government programs.
Represent Radical Numerics in scientific and industry environments, establishing credibility and trust with institutions that control critical data assets.
Data acquisition strategy
Work closely with internal scientists and ML engineers to understand which datasets most improve model capability.
Evaluate dataset quality, scale, coverage, and modality diversity to prioritize acquisitions.
Negotiation and dealmaking
Structure and negotiate agreements that unlock access to datasets while navigating regulatory, privacy, ethical, and IP considerations.
Work alongside legal and compliance teams to close data-sharing and licensing agreements efficiently.
Pipeline development
Build and maintain a global pipeline of potential data partnerships.
Identify emerging programs, consortia, and initiatives where early engagement could secure long-term data access.
Strong domain knowledge in genomics, sequencing, and imaging technologies, with intuition for what makes a dataset valuable for training large-scale biological models.
Proven ability to build relationships across biotech, pharma, hospitals, research institutes, or global scientific networks.
Experience securing access to datasets, partnerships, or collaborations in life sciences or healthcare.
Excellent negotiation and communication skills with both scientific and business stakeholders.
Comfort operating in ambiguous environments and navigating complex institutions to unlock opportunities.
Most importantly, we are looking for someone who is relentless in pursuing data: someone who will fly across the world to meet the people who control the datasets that will power the future of biological AI.
Prior roles in business development, partnerships, or data licensing in biotech or healthcare.
Experience working with international research collaborations or large scientific consortia.
Familiarity with regulatory environments around health data and genomics (HIPAA, GDPR, etc.).
Prior academic or industry research experience with genomics or multi-omics datasets.
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
- Deep domain knowledge in genomics, sequencing, and imaging technologies
- Proven ability to build relationships across biotech, pharma, hospitals, research institutes, or global scientific networks
- Experience securing access to datasets, data partnerships, or collaborations in life sciences or healthcare
- Strong negotiation and communication skills with scientific and business stakeholders
- Experience structuring and negotiating data-sharing, licensing, and partnership agreements considering regulatory, privacy, ethical, and IP constraints
- Willingness and ability to travel internationally and meet partners face-to-face
- Comfort operating in ambiguous environments and navigating complex institutions
- Prior business development, partnerships, or data licensing experience in biotech or healthcare
- Experience with international research collaborations or large scientific consortia
- Familiarity with health data regulatory environments (HIPAA, GDPR)
- Prior academic or industry research experience with genomics or multi-omics datasets
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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