Research, Mid-Training

Tech Stack

Responsibilities

• Design and iterate on high-quality data mixtures for late-stage and annealing training runs, developing principled methods for sourcing, filtering, and weighting data.
• Drive targeted improvements in coding, mathematics, and long-horizon reasoning through curated data strategies and training interventions.
• Develop and evaluate synthetic data pipelines that generate training signal at scale, understanding limits and failure modes.
• Research and optimize multi-stage learning rate schedules, warmup strategies, and compute allocation across training phases.
• Build evaluations that distinguish real capability improvements from benchmark overfitting, closing the loop between training decisions and deployment impact.

Culture

Requirements