Research Engineer, Universes
Core
Building next-generation training environments for capable and safe agentic AI, focusing on reinforcement learning and evaluating genuine capability.
Role type
Research Engineer (RL environments & agentic AI)
Builds
Novel training environments for long-horizon agentic tasks and rigorous evaluation frameworks
Domain
Artificial Intelligence / Reinforcement Learning / Agentic Systems
Deliverable
production ML models
Required skills
Reinforcement learning, software engineering, ML infrastructure, distributed systems, sandboxing, containerization, VM infrastructure, pair programming, research implementation
Preferred skills
Large language model training, fine-tuning, evaluation, simulation systems, published influential work in ML
Technologies
None explicitly listed
Responsibilities
Build next generation of agentic environments, Build rigorous evaluations that measure real capability, Collaborate across research and infrastructure teams to ship environments into production training, Debug and iterate rapidly across research and production ML stacks, Contribute to research culture through technical discussions and collaborative problem-solving
Seniority
Senior, hands-on IC
