Responsibilities
- Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
- Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
- Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI.
- Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
- Collaborate to translate experimental requirements into production-ready infrastructure
- Develop large scale data pipelines to handle advanced language model training requirements
- Optimize large scale training and inference pipelines for stable and efficient reinforcement learning
Team
Structure: organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier.
