Genmo is a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Create high-quality videos with Mochi. Backed by NEA.
About the role
We are seeking an exceptional Research Scientist to join our team, focusing on alignment and post-training techniques for large-scale video generation models. In this role, you will be at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate and safe outputs that match human preferences and values.
What they're looking for
- 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
More about this role
We are Genmo, a research lab developing the world’s most sophisticated video world models to understand, simulate, and interact with the physical world. Our mission is to unlock the right brain of AGI. Join us in advancing physical intelligence and enabling robots to learn and act in a changing world.
We are seeking an exceptional Research Scientist to join our team, focusing on alignment and post-training techniques for large-scale video generation models. In this role, you will be at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate and safe outputs that match human preferences and values.
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
Develop robust evaluation frameworks to measure model alignment, safety, and output quality
Create and optimize data collection pipelines for human feedback and preferences
Design and conduct experiments to validate alignment techniques...
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