Teams at Prime Intellect

Lead applied AI research programs in New York, combining hands-on work in reinforcement learning, post-training, agents, evaluation, and deployment. Establish research agendas, personally drive high-stakes experiments, recruit and develop researchers, set technical standards, and translate successful partner programs into shared research or product capabilities. The role is externally facing and requires strong experimental judgment, technical depth, Python expertise, and experience leading applied research or research-engineering teams.

Build post-training and agent systems for public-sector and regulated environments. Develop private improvement loops, permissioned tool-using agents, high-assurance evaluations, and deployable model updates within strict data and infrastructure boundaries. Conduct experiments, inspect traces, establish meaningful baselines, attribute failures, and collaborate directly with customers and research partners. The role requires hands-on model-training or agent experimentation, strong Python skills, sound research judgment, and comfort solving ambiguous problems.

Build environments, agents, evaluations, reward systems, and post-training methods for quantitative research and systematic decision-making. Develop realistic market and portfolio simulations, train long-horizon research agents, assess out-of-sample robustness, and create production feedback loops with monitoring and failure attribution. Collaborate directly with customers and research partners while maintaining a substantive research agenda.