- Currently pursuing a PhD in computer science, machine learning, or a related field.
- A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas.
- Experience developing and evaluating large-scale models or machine learning systems.
- Familiarity with distributed training, large-scale inference, or multi-GPU environments.
- Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR.
- Strong programming and engineering skills, with the ability to translate research ideas into working implementations.
- A collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.