Research Engineer - Reinforcement Learning

Role overview Advance reinforcement learning research and engineering for large-scale AI systems. You’ll help build synthetic data generation and orchestration capabilities, improve inference efficiency, and develop open tools that support distributed RL and model training.

Responsibilities - Research and build scalable pipelines for generating synthetic data. - Improve inference performance, cost, and resource use through compute and memory optimizations. - Develop open-source libraries for synthetic data generation and distributed reinforcement learning. - Publish research findings in leading AI venues. - Explain technical results through accessible writing for developers and customers.

Requirements - Strong research and engineering ability in reinforcement learning or a closely related area. - Experience building large-scale data generation or model training systems. - Knowledge of methods for optimizing inference compute and memory use. - Ability to contribute to production-quality open-source frameworks. - Strong technical communication skills, including writing for varied audiences.

Benefits and work setup - Full-time role with San Francisco or remote work options.