Key Responsibilities
- Design and implement reinforcement learning algorithms for complex decision-making systems
- Develop scalable training pipelines for large-scale RL models
- Collaborate with cross-functional teams to integrate RL solutions into production systems
- Optimize algorithms for performance, stability, and real-world applicability
- Publish research findings in top-tier conferences and journals
- Mentor junior researchers and engineers in RL methodologies
Requirements
- 5+ years of experience in reinforcement learning or related fields
- Strong proficiency in Python and PyTorch/TensorFlow
- Proven track record of publishing RL research in peer-reviewed venues
- Experience with distributed training and optimization techniques
- Solid understanding of deep learning fundamentals and algorithm design