Research Intern

📋 Description

• Research and develop distillation methods for large-scale diffusion and flow-based video generation
• Explore techniques that reduce inference cost while preserving or improving generation quality
• Develop reward models and preference-based optimization methods to improve aesthetics, motion
• Study how base-model behavior affects post-training outcomes and use experimental findings to
• Design rigorous evaluations and conduct large-scale experiments on generative video models
• Contribute to evaluation harnesses, model integrations, research tooling, or other product-adjacent

🎯 Requirements

• Currently pursuing a PhD or are a final-year master’s student in computer science, machine
• Research experience in generative modeling, computer vision, multimodal learning, or video
• Hands-on experience with diffusion models, flow-based models, model distillation, reinforcement
• Ability to formulate hypotheses, design controlled experiments, analyze results, and communicate
• Proficient in Python and hands-on experience with PyTorch, JAX, or another modern machine learning
• Comfortable working independently on an open-ended research problem while collaborating closely

🎁 Benefits

• A defined project and named senior mentor before your first day
• Weekly one-on-one meetings and clear project milestones
• A meaningful compute allocation for your research
• The opportunity to own a complete research or engineering result
• First-author positioning by default where your contribution supports a publication
• Timely internal review of research intended for submission