Researcher, Synthetic RL
About the Team
The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology.
About the Role
As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems.
We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Research and develop reinforcement learning algorithms
Design and run experiments to study training dynamics and model behavior at scale
Collaborate with engineers and researchers to integrate successful approaches into model training pipelines
You might thrive in this role if you:
Have a strong background in reinforcement learning, machine learning research, or related fields
Have strong engineering and statistical analysis skills
Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving
Are motivated by seeing research ideas influence real-world AI systems
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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