Agent Post-Training, Frontier Evals and Environments Research
Researcher building frontier RL environments, evaluations, and training signals to steer OpenAI's largest agent training runs and measure model capabilities.
This is a research role focused on building models that continuously evolve with the world, with a focus on efficiency, gradient-free exploration, real-time learning, and interface design. The role requires strong programming skills and expertise in model optimization techniques.
Sweat the details. Technical excellence requires obsessing over every detail. We co-design serving, algorithms, and interface as one system to maximize efficiency and enable real-time adaptation.
Move with conviction. Extraordinary results require extraordinary effort. We operate with urgency as a unified team, concentrating resources on a few high-conviction bets where research and impact intersect.
Metrics that matter. The most intelligent system will increasingly be defined by building an algorithm that can interact with the world. Research ideas are tested through working products. If it doesn't improve what users can do, we question whether it matters. We share what moves the field; we don't optimize for paper count.
This is a research role focused on building models that continuously evolve with the world. Our frontier work centers on efficiency, gradient-free exploration, real-time learning, and interface design. The most intelligent systems will increasingly be defined not just by what they know, but by how well they can interact with the world. For the first time, researchers who care deeply about intelligence and efficiency must also be obsessed with the interface through which a model acts. If any of this resonates, we'd love to hear from you.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.
Researcher building frontier RL environments, evaluations, and training signals to steer OpenAI's largest agent training runs and measure model capabilities.
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