Staff Scientist: Protein Structure Modeling & Genomics AI

Radical Numerics; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Radical Numerics is seeking a Member of Technical Staff focused on protein structure modeling. You will develop advanced ML systems to understand and predict protein structures, working at the intersection of large-scale biological models, geometric deep learning, and structural biology.

Expect hands-on model implementation, large-scale experiments, and careful evaluation of scientific performance. You will collaborate with researchers across ML, computational biology, and engineering to

Qualifications

• Experience developing ML models for protein structure prediction or related structural biology tasks.
• Experience training or fine-tuning protein language models or structure models.
• Knowledge of geometric neural networks and equivariant architectures.
• Familiarity with protein structure metrics and evaluation practices.
• Ability to design rigorous experiments and analyze results.

Responsibilities

• Develop and improve ML models for protein structure prediction and related tasks.
• Train and fine‑tune protein language models and geometric diffusion architectures.
• Build data pipelines and evaluation systems for structural modeling.
• Design benchmarks to measure generalization and minimize data leakage.
• Collaborate with researchers across ML, computational biology, and engineering.

Skills

Protein structure modeling

Geometric deep learning

Experiment design

Scientific communication

Education

PhD or equivalent in ML/CS/biophysics

Tools

PyTorch

JAX

Job description

Radical Numerics is seeking a Member of Technical Staff focused on protein structure modeling. You will develop advanced ML systems to understand and predict protein structures, working at the intersection of large-scale biological models, geometric deep learning, and structural biology.

Expect hands-on model implementation, large-scale experiments, and careful evaluation of scientific performance. You will collaborate with researchers across ML, computational biology, and engineering to