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About the Role

You will build the application surface for your area of ownership, including interactive workbenches, variant scoring and ranking pipelines, and other tools that make model output usable by scientists unfamiliar with our API. You will run our models on partner data and present results with enough interpretability for a computational biologist to trust the output. You will build the evaluation infrastructure that makes our claims verifiable. You will present your own work directly in partner meetings, field technical objections in real time, and return with fixes. Expect to ship on a weekly cadence.

Responsibilities

Develop the application surface for your area of ownership, including interactive workbenches, variant scoring and ranking pipelines, and other tools that make model output usable by scientists unfamiliar with our API.
Run our models on partner data and present results with enough interpretability for a computational biologist to trust the output — or clearly articulate why they don't.
Build the evaluation infrastructure that makes our claims verifiable, including held-out benchmarks, blind retrospectives on solved cases, and head-to-head comparisons against tools partners currently use.
Present your own work directly in partner meetings, field technical objections in real time, and return with fixes.
Ship on a weekly cadence.
Most features begin as prototypes developed live in partner conversations.

Requirements

You build across the stack.
Python for data and model work, TypeScript and React for the interfaces with equal facility in either depending on what the week demands.
You have worked with real genomic data.
VCFs, reference builds, variant annotation, and the specific ways this data is messy in practice.
Comfortable engaging a partner's computational biology team as a technical peer, including in skeptical or challenging technical discussions.
Comfortable operating without a finished spec — able to take a rough direction and a partner conversation and turn them into a working system within a week.

Skills

Python
TypeScript
React
Genomic data
VCFs
Reference builds
Variant annotation

About the Company

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.

Equal Opportunity

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.