Member of Technical Staff, AI Bio

About the role

Radical Numerics is seeking research scientists and engineers to advance AI architectures for biological problems. You will adapt large foundation models to tasks in genomics, protein biology, and cellular systems, collaborating across computational biology and systems architecture teams.

Key responsibilities

• Adapt frontier AI models to biological tasks through fine‑tuning, adapters, and architectural modifications.
• Design and run experiments applying large models to genomics, regulatory biology, protein biology, or cellular systems.
• Develop evaluation pipelines and benchmarks for tasks such as variant interpretation, gene regulation modeling, and protein function prediction.
• Analyze model behavior, run ablations, and explore interpretability pipelines for biological discovery.

Required profile

• Strong background in machine learning and deep learning for large‑scale generative architectures.
• Experience adapting large models to new domains via fine‑tuning, post‑training, or architecture changes.
• Familiarity with molecular biology data modalities (genomics, gene regulation, protein or cellular systems).
• Mid‑to‑senior level experience building and deploying ML systems in research or production.

Required skills

• Python programming.
• ML frameworks such as PyTorch or JAX.
• Experience with distributed training and experiment management tools.