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Reinforced Learning in New York, NY seeks a frontend engineer to build fast, dense interfaces for reviewing trajectories, diffs, and rubrics. You will own keyboard-first workflows and optimize performance for large content, while contributing to a shared component library used across tools.
You will collaborate with quality and research teams, focusing on user-centered design and precise UI to support reviewers and editors in complex review tasks.
Reviewers compare trajectories, read diffs, grade against rubrics and adjudicate disagreements for hours at a time. The interface determines how accurate they are. You’ll build it to be fast, dense and kind to attention.