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Radical Numerics

Develops multimodal foundation models for biology

Applications Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Build across the stack using Python for data and model work and TypeScript, React, or similar technologies for interfaces.
  • Have experience working with real genomic data, including VCFs, reference builds, and variant annotation, and understand its practical data-quality challenges.
  • Engage a partner's computational biology team as a technical peer in skeptical or challenging technical discussions.
  • Operate without a finished specification and turn rough direction and partner conversations into a working system within a week.

Responsibilities

  • Develop the application surface for the area of ownership, including interactive workbenches, variant scoring and ranking pipelines, and tools that make model output usable by scientists unfamiliar with the API.
  • Run models on partner data and present results with enough interpretability for a computational biologist to trust the output.
  • Build evaluation infrastructure to make claims verifiable, including held-out benchmarks, blind retrospectives on solved cases, and head-to-head comparisons against tools partners currently use.
  • Present work directly in partner meetings, field technical objections in real time, and return with fixes.
  • Ship on a weekly cadence, with most features beginning as prototypes developed live in partner conversations.

Desired Qualifications

  • Experience designing model evaluations and a point of view on what makes a benchmark honest.
  • Experience handling sensitive human data under strict access controls and understanding its limits.
  • A forward-deployed engineering, solutions engineering, or founding engineer background at an AI or infrastructure company.

About the Company

Radical Numerics

Develops multimodal foundation models for biology

Radical Numerics is an AI research lab that builds multimodal foundation models for biology to enable generative genomics for medicine and biodefense. Its Evo and Evo 2 models are open biological sequence models trained on millions of genomes, while Omnii is a genome language model with a two-million-token context, multimodality, and alignment that is being piloted for early cancer detection and biosurveillance. The company differentiates itself by focusing on large, multimodal biology models and dual-use health and biodefense applications, often partnering with industry and government labs. Its goal is to scale compute and architecture research to advance practical deployments in human health and biodefense.

Company size
11-50
Company stage
Seed
Total funding
$50M
Headquarters
San Francisco, CA
Founded
2025

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