About Us

Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions. Our founding team has previous experience on Anthropic’s data team building data infrastructure, and datasets behind Claude. We are partnering with leading AI labs to push AI closer to achieving its transformative potential.

About The Role

We’re hiring experienced ML Engineers to design and build reinforcement learning environments to safely advance model capabilities specifically on machine learning research and engineering tasks to do the work of an MLE at a frontier lab. This role blends research and engineering. It will require you to both develop novel approaches and realize them in code. Your work will...