Applied Research Sovereign AI

AI infrastructure company providing an integrated stack for training, evaluating, deploying, and continuously improving agentic models.

Series ARecently funded34 current maintainers27 active leads7 new active leads9 lead step-downs
San Francisco, United States
About Prime Intellect

Prime Intellect, Inc. operates AI infrastructure spanning RL environments, hosted training and evaluations, inference, secure sandboxes, and globally sourced GPU compute.

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Skills

About the Role

You will build post-training and agent systems within strict data, deployment, access, auditability, and human-authority boundaries. You will create private improvement loops, permissioned and traceable agents, and evaluations for reliability, calibration, recovery, and compliance.

Requirements

  • Experience in reinforcement learning, post-training, private ML systems, high-assurance evaluation, agent safety, regulated-domain ML, public-sector technical work, or constrained deployment
  • Experience building and debugging model-training, post-training, agent, or evaluation loops
  • Experimental judgment, including baselines, trace inspection, and failure attribution
  • Python
  • Ability to build reproducible artifacts for researchers and engineers
  • Ability to own ambiguous problems and communicate with partners

Responsibilities

  • Build end-to-end improvement loops inside operator data and infrastructure boundaries
  • Develop agents with explicit permissions, evidence trails, bounded tools, and human checkpoints
  • Design evaluations for reliability, calibration, recovery, and compliance with real procedures
  • Study how privacy, access, and infrastructure constraints affect learning

Benefits

  • Flexible work
  • Visa sponsorship and relocation support
  • Team off-sites and conference attendance