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-generated 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 Role
You'll own recruiting across Radical Numerics, running every search end to end, from first outreach through signed offer. Our team hires AI/ML researchers, engineers, and operators, so you'll be finding and closing talent across a wide range of disciplines, often for roles where the right person is rare and in high demand.
You'll own the entire process: sourcing, pipeline management, candidate experience, logistics, and close. That means building relationships with candidates long before they're ready to move, keeping searches organized and moving quickly, making sure every person who interviews with us walks away with a great impression.
We're a team of about 35, which means the hiring practices you establish now will become the foundation the company relies on as it scales. Beyond running searches, you'll be building the recruiting function itself: defining how we evaluate candidates, setting the standard for how we communicate with them, and creating processes that stay rigorous and personal as we grow.
What You'll Do
Run full-cycle searches from sourcing and first screen.
Source and engage candidates directly, and handle inbound interest.
Design and coordinate interview loops, including panels, reschedules, and candidate confirmations.
Schedule and coordinate reference checks with hiring managers and co-founders.
Draft and send offer letters in Ashby and assist in offer negotiations.
Close every search cleanly. Send thoughtful rejections and keep strong candidates warm for future roles.
Publish job postings on a monthly cadence, including Hacker News "Who's Hiring" on the first weekday of each month and any other relevant forums.
Run pre-immigration surveys for candidates and hand off to People Ops when a visa path is needed.
Own the Ashby hiring dashboard and report on pipeline health, conversion, and time to hire.
Build the intake, calibration, and debrief practices the company will rely on as hiring volume grows.
What We're Looking For
You have personally run full-cycle searches for technical roles, ideally ML researchers, engineers, or scientists, and can walk through how you closed your hardest hire.
You are proficient in both G&A and Technical Recruiting.
5+ years of recruiting experience at a fast-paced, high growth startup.
You are credible with technical candidates. You understand the work well enough to pitch it and to tell when a candidate's profile doesn't hold up.
You are fluent in Ashby or a comparable ATS and keep your data clean enough that the dashboard can be trusted.
You treat candidate experience as a competitive advantage. People should want to join after interviewing with us, even if they decline.
You are comfortable building a process where none exists yet.
You are excited about building a generational company at the intersection of AI and biology.
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
- 5+ years of recruiting experience at a fast-paced, high-growth startup
- Experience independently running full-cycle searches for technical roles
- Proficiency in both G&A and technical recruiting
- Ability to build credibility with technical candidates and evaluate technical profiles
- Fluency in Ashby or a comparable applicant tracking system
- Experience recruiting ML researchers, engineers, or scientists
- Ability to build recruiting processes from scratch
- Strong candidate experience and communication skills
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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