Agent Post-Training, Computer Use Research

Tech Stack

Responsibilities

• Design and run experiments to improve agentic model behavior for complex computer use, including desktop and browser.
• Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.
• Build evals and environments that expose new model failures and translate them into training data, product fixes, or new research directions.
• Partner with product teams to understand user needs and translate product signals into model improvements.
• Improve the machinery for large-scale training and launch, focusing on experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.

Culture

Requirements