ML Systems Engineer, RL Engineering

Lead the design, development, and maintenance of the algorithms and infrastructure used to train models with reinforcement learning and RLHF. Improve speed, reliability, and usability of training systems; optimize large-scale RL pipelines; profile and diagnose performance bottlenecks; and implement new training algorithms for evolving model architectures. Build and launch training jobs in test environments to quickly detect pipeline issues and ensure robust operations. Collaborate with researchers and engineers to enable faster breakthroughs while maintaining safety and steerability. Instrument training workflows for observability, diagnose GIL contention, and improve developer productivity. This role emphasizes impact, flexibility, and cross-functional teamwork in a fast, research-driven environment.