Member of Technical Staff, Pretraining Science

About the role

Radical Numerics is seeking a Member of Technical Staff to advance the science of pre‑training biological foundation models. You will bridge theory and implementation, designing experiments and high‑performance code to improve large‑scale model learning.

Key responsibilities

• Research and develop new pre‑training methodologies, objectives, and data curricula for multimodal biological data.
• Study scaling behavior across model size, data composition, context length, and compute budget, and translate findings into training recipes.
• Design, execute, and rigorously analyze large‑scale experiments, ensuring reproducibility and robust instrumentation.
• Collaborate with infrastructure and data teams to optimize distributed training pipelines.

Required profile

• Strong track record in machine‑learning research or engineering, especially large‑scale model training and representation learning.
• Proven ability to design, run, and interpret experiments with empirical rigor.
• Excellent written and verbal communication skills for cross‑disciplinary collaboration.

Required skills

• Python programming.
• Deep‑learning frameworks, primarily PyTorch.
• Experience with distributed or high‑performance computing environments.

What we offer

• Competitive compensation and comprehensive benefits.
• Support for continual learning and professional development.
• Opportunity to work on cutting‑edge AI for biological science.