Principal Researcher – Reinforcement Learning for Large Foundation Models

Key Responsibilities
1.Lead in conducting cutting-edge algorithm research, with a focus on the design and optimization of RL algorithms for large foundation models. Research areas include but are not limited to Reinforcement Learning Algorithms, Reward Modeling, and World Models.
2.Conduct large-scale experiments of RL algorithms in scenarios such as complex reasoning and autonomous agents, deliver impactful algorithms for real world applications, and publish influential research papers.
3.Explore frontier technologies in large foundation models, and provide technical solutions aligned with future practical application scenarios.
 
Work Location: US-Washington-Bellevue

Qualifications
1.Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields from a top university.
2.Experience of working in leading global companies in the field of large foundation models.
3.Proficient in Python programming and experienced in developing with deep learning frameworks such as PyTorch or TensorFlow.
4.Strong academic background, with publications in top-tier conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP; experience in deep learning research or engineering projects.
5.Excellent communication and teamwork skills, capable of collaborating with cross-functional teams to drive project success and innovation.。加分项：