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Research Engineer/Scientist, Reinforcement Learning

Prime Intellect • United State
Remote Visa Sponsorship Relocation
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Develop algorithms and systems to train open superintelligence models using reinforcement learning. Focus on RL methods for reasoning, scaling science, and improving distributed training frameworks. Requires deep expertise in RL algorithms, PyTorch, and distributed ML systems.

Key Highlights
Develop RL methods for reasoning, coding, and long-horizon tasks
Design scaling experiments to optimize model size and training compute
Extend the prime-rl framework to support asynchronous training workflows
Key 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 and trainer/sampler mismatch.
Collaborate with data and evaluation researchers to understand the impact of task selection and rewards on model learning.
Design experiments to understand how RL performance changes with model size, training compute, and task horizon.
Turn experimental findings into training recipes and test them across larger models.
Extend prime-rl to support new algorithms, models, and asynchronous training workflows.
Improve performance and numerical correctness of research runs across trainers and rollout workers.
Build diagnostics to make unstable runs and performance regressions easier to reproduce.
Technical Skills Required
Python PyTorch Reinforcement Learning
Benefits & Perks
Cash Compensation Range of $150-350k
Equity incentives
Flexible work arrangements
Visa sponsorship
Relocation assistance
Quarterly team off-sites, hackathons, and conferences
Nice to Have
Experience with distributed training frameworks or asynchronous rollout pipelines
Experience diagnosing unstable RL runs, including policy-staleness or numerical issues
Work on coding agents, verifiable rewards, or long-horizon environments

Job Description

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
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