Research Scientist (post-training)
Genmo · San Francisco, CA · 8 mo ago
On-siteOTHRFull-time
Key responsibilities
- Lead research initiatives in alignment and post-training methods for video generation models, focusing on improved quality, reliability, and adherence to human intent
- Design and implement supervised fine-tuning and reinforcement learning from human feedback (RLHF) pipelines for video generation models
- Create and optimize data collection pipelines for human feedback and preferences
- Design and conduct experiments to validate alignment techniques and their scaling properties
- Collaborate with cross-functional teams to integrate alignment improvements into our production pipeline
- Stay at the cutting edge of the field by regularly reviewing academic literature in both generative AI and alignment
- Mentor junior researchers and foster a culture of responsible AI development
- Work closely with product teams to ensure alignment methods enhance rather than inhibit model capabilities
Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field
- Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR) with a focus on reinforcement learning, alignment, or generative models
- Extensive experience implementing and optimizing large-scale training pipelines using PyTorch
- Deep understanding of reinforcement learning techniques, particularly RLHF
- Experience with distributed training systems and large-scale experiments
- Proven track record in designing and implementing robust evaluation frameworks
- Excellent communication skills with the ability to explain complex technical concepts to diverse audiences
- Strong software engineering skills and experience with complex shared codebases
- Experience with diffusion models or other generative architectures
- Background in fine-tuning large language models or generative models
- Experience working with human feedback data collection and annotation pipelines
- Strong aesthetic sense and understanding of video quality assessment
- Familiarity with alignment techniques such as constitutional AI or debate
- Track record of successful collaboration with product teams
- Experience with perceptual quality metrics and human evaluation design
- Contributions to open-source projects in AI alignment or generative AI