- New York City, New York, United States +1 more
- Hybrid
- Full-time · Senior
- $200K–$375K per year
Advance reinforcement learning for large language models, developing, implementing, and running training methods to help models solve frontier-level challenging tasks.
Locations (2)
- New York City, New York, United States
- San Francisco, California, United States
Compensation
$200,000—$375,000 USD
Responsibilities
- Research and implement cutting-edge reinforcement learning algorithms and training recipes for large language models, adapting and extending methods such as GRPO for complex, multi-turn, and long-horizon tasks
- Design and build data pipelines that generate high-quality training signals for RL workflows, including AI-assisted data annotation and curation data pipelines to improve model generalization to unseen benchmarks
- Prototype and iterate on end-to-end RL training recipes, using training and evaluation results to identify what improves performance and where tasks, environments, or training signals need to change