Key Responsibilities
- Research and develop novel diffusion model architectures and training techniques
- Publish findings in top-tier conferences and journals
- Collaborate with engineering teams to transition research into production
- Explore advanced topics in generative modeling and sampling methods
- Design and conduct experiments to validate theoretical hypotheses
- Mentor junior researchers and contribute to the research community
Requirements
- PhD or equivalent experience in machine learning, computer science, or related fields
- Strong publication record in generative modeling or diffusion models
- Expertise in PyTorch/TensorFlow and mathematical modeling
- Deep understanding of probability theory, optimization, and numerical methods
- Experience with high-performance computing and distributed training