The opportunity
As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both…
What you'll do
Developing systems that enable models to use computers effectively
Advancing code generation through reinforcement learning
Pioneering fundamental RL research for large language models
Building scalable RL infrastructure and training methodologies
Enhancing model reasoning capabilities
Architect and optimize core reinforcement learning infrastructure, from clean: training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows.
What they're looking for
- Design, implement, and test novel training environments, evaluations, and: methodologies for reinforcement learning agents which push the state of the art for the next generation of models.
- Drive performance improvements across our stack through profiling,: optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows.
- Collaborate across research and engineering teams to develop automated: testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research.
- Are proficient in Python and async/concurrent programming with frameworks like Trio
