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Radical Numerics
San Francisco, California, United States • On-site
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You will lead the discovery side of the business by identifying and closing partnerships with pharma R&D organizations. You are responsible for defining product strategy for target discovery and validation while managing commercial targets.
The ideal candidate possesses deep expertise in human genetics and the pharma discovery workflow, including experience selling to scientific buyers. You must be comfortable working in a technical environment and capable of translating scientific benchmarks into commercial success.
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.
You own the discovery side of our business. You identify where in pharma orgs our deals get funded, including discovery, data science, and therapeutic areas.
Our science team owns the model itself. You decide what we build on top of it for target discovery and validation. The people who evaluate us are genetics and computational biology groups, and they don't move without evidence, so you will have a lot of say in which benchmarks 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 from early on.
Decide which applications of the model matter for target identification and validation, and what we build first.
Originate and close partnerships with pharma discovery organizations. You are measured on committed contract value and on partners using the product week to week.
Find the internal champion, learn which budget funds a deal like ours, and give that champion what they need to get it approved.
Write the specs your engineer builds from, and stay with a partnership after signature
Tell our science team which benchmarks would move your deals, and make the case for running them.
Set pricing and structure with the Head of Product, and run the negotiation with our legal team.
Ensure key partners renew and expand.
Fluency in human genetics. GWAS, fine-mapping, burden testing, variant-to-function work. You can read a variant effect benchmark, tell whether the result means anything, and say so in front of a partner's chief scientist.
Breadth across the discovery workflow. You know what happens to a target after it is nominated, what evidence moves it forward, and what gets one killed.
You know how a large discovery organization buys. Which budget funds a platform deal, who else is competing for it, and where a collaboration dies internally.
You have sold to pharma R&D and carried a number. Deals you closed yourself, to scientific buyers.
You are comfortable as the only commercial person in a room of scientists, on both sides of the table.
You want to own revenue.
You have worked inside a pharma discovery organization.
You founded a company, or were one of the first ten people at one.
Published work in genetics, genomics, or computational 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.
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