Video-Generation AI Alignment Scientist

We Love AI Jobs; San Francisco (CA); On-site; USD 190,000 - 260,000; Full time

Job summary

Genmo in San Francisco is seeking an exceptional Research Scientist to advance alignment and post-training techniques for our diffusion-based video generation models. You will lead experiments, design RLHF and supervised fine-tuning pipelines, and collaborate with research and product teams to improve reliability and safety.

The role emphasizes rigorous evaluation, data-collection for human preferences, and close integration of research with production.

Qualifications

• PhD in CS/AI/ML or related field.
• Strong publication record in NeurIPS/ICML/ICLR.
• Experience building large-scale training pipelines with PyTorch.
• Experience with RLHF and distributed training.
• Excellent communication and software engineering skills.

Responsibilities

• Lead research initiatives in alignment and post-training methods for video generation models.
• 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 and scaling properties.
• Collaborate with cross-functional teams to integrate alignment improvements into production.
• Stay at the cutting edge by reviewing academic literature; mentor junior researchers.

Skills

PyTorch

Reinforcement learning

RLHF

Supervised fine-tuning

Diffusion models

Distributed training

Model evaluation

Human feedback data pipelines

Education

Ph.D. in Computer Science, AI, ML, or related field

Job description

Genmo in San Francisco is seeking an exceptional Research Scientist to advance alignment and post-training techniques for our diffusion-based video generation models. You will lead experiments, design RLHF and supervised fine-tuning pipelines, and collaborate with research and product teams to improve reliability and safety.

The role emphasizes rigorous evaluation, data-collection for human preferences, and close integration of research with production.