Applied Ai Scientist Simulation Reinforcement Learning Jobs in San Francisco, CA

By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come

About the teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical

AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical

& Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

We’re looking for applied scientists with a Machine Learning and Artificial Intelligence background to build AI

About the RL Teams Our Reinforcement Learning teams play a critical role in advancing our AI systems.

…on pushing the boundaries of reinforcement learning research, building next-generation generative models, and deploying them at scale.

…and test robot policies in simulation, using execution feedback, context management, and retry budgets to recover from failures.

& Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

& Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

…the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning

…years of experience working on reinforcement learning, post-training, agents, or related ML systems.

…Design and implement modern robot learning systems, including imitation learning, reinforcement learning