Research Engineer, Universes
Remote • Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
Posted 16d ago
Job Location
Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
The Universes team within Research is responsible for training AI models to perform complex, difficult, long-horizon agentic tasks in ultra-realistic settings. We design and implement novel training environments that go far beyond what models can do today — environments where models learn to navigate ambiguity, handle interruptions, maintain context over extended interactions, and exercise judgment in open-ended scenarios. We're looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability.
Responsibilities
- Build the 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
Requirements
- Highly impact-driven with a focus on outcomes
- Operate with high agency
- Possess good research taste or senior technical experience demonstrating good judgment
- Ability to balance research exploration with engineering implementation
- Passionate about the potential impact of AI and committed to developing safe and beneficial systems
- Comfortable with uncertainty and adapt quickly
- Strong software engineering skills and ability to build robust infrastructure
- Enjoy pair programming
- Industry experience with large language model training, fine-tuning or evaluation (preferred)
- Industry experience building RL environments, simulation systems, or large-scale ML infrastructure (preferred)
- Senior experience in a relevant technical field (preferred)
- Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems (preferred)
- Published influential work in relevant ML areas (preferred)
- Bachelor’s degree or equivalent combination of education, training, and/or experience