Research Scientist (AI)

Research Scientist (AI)OverviewPhysical Superintelligence is a startup with roots at Harvard, MIT, Johns Hopkins, Oxford, the Institute for Advanced Study, and the Perimeter Institute is building AI systems to discover new physics at scale. We are seeking AI researchers to develop reinforcement learning agents and training systems for scientific discovery.Role and ResponsibilitiesBuild and train AI systems for physics discovery, working with physicists who design verification harnesses and engineers who build training infrastructure. Focus on core AI research questions including how agents learn physics reasoning, action space design for scientific discovery, reward structure development, and training systems that scale.Build and train reinforcement learning agents using modern approaches including PPO, SAC, MuZero, and multi-agent self-play and other methodsDesign agent architectures for physics reasoning and scientific tool useImplement training curricula and reward structures for discovery tasksDevelop evaluation workflows and benchmarks for physics reasoning capabilities Build instrumentation to understand agent behavior and learning dynamicsCollaborate with physicists and engineers on system design and architectureWhat We're Looking ForWe seek candidates with experience building agents and training models with reinforcement learning. You should have proficiency in modern machine learning frameworks and understand distributed training systems with a track record shipping working AI systems.Core AI and machine learning skills:Hands-on experience with modern reinforcement learning algorithms including PPO, SAC, MuZero, and multi-agent self-play and other methodsProficiency with PyTorch or JAX, distributed training using Ray, XLA, or Accelerate, and modern pretraining workflowsValued backgrounds and experience: Physics or mathematics background providing intuition for physical reasoning and mathematical modelingExperience applying agents to simulators, games, scientific tool use, or benchmark design with rigorous experimental methodologyLocation and CompensationThis is an in-person role based in Boston or San Francisco. We offer competitive compensation including salary, benefits, and meaningful early-stage equity. We evaluate on AI research depth, scientific curiosity, and ability to ship working systems. We are an equal opportunity employer and value diverse perspectives in building AI for scientific discovery.

Created: 2026-04-15