Research Engineer / Scientist - Reinforcement Learning

Prime Intellect is hiring a Research Engineer / Scientist to develop algorithms and systems for training its open models with reinforcement learning. The role focuses on RL algorithm research, scaling experiments, or extending and improving RL training frameworks.

Responsibilities:

• Develop and test RL methods for reasoning, coding, and long-horizon tasks, including changes to training objectives and policy optimization
• Investigate stability in asynchronous RL, including policy staleness, trainer/sampler mismatch, and numerical differences between training and rollouts
• Work with data and evaluation researchers to understand how task selection, rewards, and training data affect what the model learns
• Design experiments to understand how RL performance and learning dynamics change with model size, training compute, and task horizon
• Use controlled ablations and evaluations to distinguish learning gains from reward exploitation, evaluation artifacts, or training bugs
• Turn experimental findings into training recipes, then test whether the improvements hold across larger models and longer runs
• Extend prime-rl to support new algorithms, models, and asynchronous training workflows
• Improve the performance and numerical correctness of research runs across trainers, rollout workers, and environments, working with the infrastructure team
• Build diagnostics that make unstable runs and performance regressions easier to reproduce, and help distinguish algorithm problems from implementation or runtime issues