Agent Post-Training, Connectors Research

Tech Stack

Responsibilities

• Design and run experiments to improve agentic model behavior for complex software and plugins.
• Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, and diagnostics.
• Build evals and environments to expose model failures, then turn those failures into training data, product fixes, or new research directions.
• Partner with product teams to translate user needs into model improvements.
• Improve the machinery for large-scale training and launch, focusing on experiment velocity, reliability, and cost.

Culture

Requirements