Member of Technical Staff, AI Engineering for Biosecurity

The role

You will lead the design, evaluation, and deployment of multimodal genome language models. The role focuses on biosecurity and biodefense efforts by translating large-scale machine learning into biological modeling capabilities.

What you will do

• Build and adapt frontier AI models through fine-tuning and post-training.
• Design and run experiments applying large models to problems relevant to biosecurity and biodefense.
• Translate technical capabilities into deployable systems like early warning platforms and sequence screening tools.
• Work with government and partners to align systems with real-world workflows.
• Analyze model behavior and run ablations to understand model reasoning and failure modes.
• Explore modern mechanistic interpretability pipelines and methods.
• Prototype new approaches for prediction and design using foundation models.
• Operate with high ownership in a fast-moving, ambiguous environment.

Required qualifications

• Strong technical background in deep learning for large-scale classification, retrieval, or generative models.
• Ability to design evaluation tasks and benchmarks.
• Strong Python and ML tooling experience (PyTorch or JAX, experiment management, distributed training).
• Experience applying ML models to biological data and challenging prediction tasks.
• Familiarity with molecular biology and biological data modalities, particularly genomics, gene regulation, protein biology, or cellular systems, or an interest in applying your AI/ML skills in this sp
• Ability to reason concretely about what biological AI systems can and cannot do, how those capabilities translate into real-world risks, and how to measure and mitigate those risks.
• High agency: defines problems, runs with them, and ships.

Nice to have

• Familiarity with multimodal biological modeling, including in genomics or protein structure.
• Experience building robust evaluation suites for large AI systems.
• Experience scaling ML experiments across large GPU clusters.
• Research publications in ML for biology, chemistry, or related areas.
• Experience in applied areas of biosecurity or biodefense, such as pathogen-agnostic detection or countermeasure development.
• Familiarity with bioinformatics algorithms and tooling like BLAST, DIAMOND, HMMER, etc.
• Experience with models like biological foundation models like Evo, ESM, AlphaFold.

Benefits

• Competitive compensation
• Comprehensive benefits
• Support for continual learning

Before you apply

• Radical Numerics participates in E-Verify to confirm authorization to work in the U.S.

About the company

Radical Numerics is an AI research lab building general biological intelligence. Their mission is to master the code of life to reduce human suffering.