Research Engineer, Mid-Training

Cognition, San Francisco

What you will do

Data Mix and Quality Uplift: Design and iterate on high-quality data mixtures for late-stage and annealing training runs. Develop principled methods for sourcing, filtering, and weighting data to sharpen model capabilities without degrading general performance.
Capability Injection: Drive targeted improvements in coding, mathematics, and long-horizon reasoning through curated data strategies and training interventions. Translate research insights into measurable capability gains on our agents.
Synthetic Data Research: Develop and evaluate synthetic data pipelines that generate training signal at scale. Understand the limits and failure modes of synthetic approaches and build methods that hold up in production training runs.
Annealing and Schedule Design: Research and optimize multi-stage learning rate schedules, warmup strategies, and compute allocation across training phases. Understand how schedule choices interact with data distribution and model behavior.

Cognition, San Francisco

Data Mix and Quality Uplift: Design and iterate on high-quality data mixtures for late-stage and annealing training runs. Develop principled methods for sourcing, filtering, and weighting data to sharpen model capabilities without degrading general performance.
Capability Injection: Drive targeted improvements in coding, mathematics, and long-horizon reasoning through curated data strategies and training interventions. Translate research insights into measurable capability gains on our agents.
Synthetic Data Research: Develop and evaluate synthetic data pipelines that generate training signal at scale. Understand the limits and failure modes of synthetic approaches and build methods that hold up in production training runs.
Annealing and Schedule Design: Research and optimize multi-stage learning rate schedules, warmup strategies, and compute allocation across training phases. Understand how schedule choices interact with data distribution and model behavior.