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Research Engineer / Scientist - Reinforcement Learning

Prime Intellect· Research
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San Francisco, Remote$150k - $350kFull-timePosted 4d ago

About the role

Role focused on developing algorithms and systems to train Prime Intellect’s open models with reinforcement learning, spanning RL algorithms, scaling research, and training frameworks within a frontier-open AI platform.

Responsibilities

  • Algorithm research: 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.
  • Scaling science: 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.
  • RL frameworks: 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.

Qualifications

  • Demonstrated depth in at least one of RL algorithms, empirical research on model training, or distributed ML systems.
  • Strong programming skills in Python and experience with PyTorch or a comparable ML framework.
  • Ability to design controlled experiments, interpret results, and debug unexpected model or system behavior.
  • Experience taking a research idea or systems change through implementation, testing, and evaluation, with a clear account of what worked and what didn’t.

Skills

Required:Reinforcement LearningPythonPyTorch or comparable ML frameworkExperiment design and analysis
Nice to have:Systems and scalable ML

Benefits

  • Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.
  • Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.
  • Visa sponsorship and relocation assistance for international candidates.
  • Quarterly team off-sites, hackathons, conferences and learning opportunities.
  • Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
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