Applied Research Scientist

This role is within the Agent Data and Optimization team. The team is the Applied AI org’s data and research environment engine: we turn world-class technical expertise into the training data, reinforcement learning (RL) environments, evaluations, and feedback loops that make […]’s models and the products built on them the best in the world. Our research and agentic work directly improves Muse family of models and powers products such as Muse Code and the Muse assistant.

This unique data and research infrastructure is a key differentiator for […], complementing our investments in compute and model architecture. Why this is exciting: You’ll work directly on frontier AI models, not adjacent to them. We’re a significant, well-funded organization with the ethos of an AI startup: new, highly entrepreneurial, flexible, and already delivering measurable impact.

Research and RL environments from our team went directly into the latest Muse release and helped the Muse family of models compete at the frontier. As a Research Scientist, you’ll independently own ambitious applied research from question to measured result. You’ll identify capability gaps, formulate hypotheses, develop methods and benchmarks, build experimental environments and high-quality RL environments, and analyze agent behavior to distinguish genuine progress from shortcuts.

The work centers on advancing AI through: - Original research that develops agents’ ability to reason, experiment and solve complex technical pr