Member of Technical Staff, Pre-Training Science at radical-numerics

Department: R&D

Setup: On-site
Location: San Francisco, California
Level: senior
Posted: Mar 17, 2026

Description

Radical Numerics is hiring a Member of Technical Staff, Pre-Training Science to advance the science of large-scale biological world models. The role combines research and engineering to develop new pretraining methods, study scaling behavior, design data curricula and sampling strategies, improve architectures and optimization, run large-scale experiments, and build evaluation frameworks. Candidates should have a strong track record in machine learning research or engineering, experience with distributed or high-performance computing, and proficiency in Python and PyTorch.

Required Skills

Python
PyTorch
Distributed computing
Representation learning
Scaling laws
Data selection
Evaluation frameworks

Additional Information

Required Previous Experiences: Strong track record in machine learning research or engineering, especially in large-scale model training, pretraining, representation learning, optimization, or scaling laws
Experience working in distributed or high-performance computing environments
Preferred Qualifications: Experience training or analyzing frontier or foundation models
Strong grasp of probability, statistics, optimization, and machine learning fundamentals
Familiarity with curriculum learning, data selection, active learning, or data-quality methods for large-scale training
Experience designing or maintaining evaluation frameworks for large models
Contributions to open-source machine learning systems, datasets, or research tooling
Background in applied mathematics, systems, computational biology, physics, mathematics, or another strongly quantitative field