Research Intern
Research Intern working on next-generation video generation models through experimentation in distillation, inference efficiency, reward modeling, preference optimization, and scalable training infrastructure. Applicants should be pursuing a PhD or final-year master’s degree with relevant research experience and strong Python and machine learning framework skills.
About the job
Responsibilities
- Research and develop distillation methods for large-scale diffusion and flow-based video generation models, including guidance and adversarial distillation.
- Explore techniques to reduce inference cost while preserving or improving generation quality.
- Develop reward models and preference-based optimization methods for aesthetics, motion quality, temporal consistency, and prompt adherence.
- Study how base-model behavior affects post-training outcomes and apply findings to model development.
- Design rigorous evaluations and conduct large-scale experiments on generative video models.
- Contribute to evaluation harnesses, model integrations, research tooling, and related product-adjacent projects.
- Document and communicate findings through research reports, internal presentations, demonstrations, and potential conference submissions.
Requirements
- Currently pursuing a PhD or in the final year of a master's program in computer science, machine learning, computer vision, or a related field.
- Research experience in generative modeling, computer vision, multimodal learning, or video generation.
- Hands-on experience with diffusion models, flow-based models, model distillation, reinforcement learning, preference optimization, or related post-training techniques.
- Ability to formulate hypotheses, design controlled experiments, analyze results, and communicate conclusions clearly.
- Proficiency in Python and hands-on experience with PyTorch, JAX, or another modern machine learning framework.
- Ability to work independently on open-ended research problems while collaborating with mentors and the broader team.
Nice to Have
- Experience with video, image, audio, or other multimodal data.
- Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or AAAI.
Compensation and Benefits
- Competitive monthly stipend.
- Visa and travel support for eligible international candidates.
- Housing support for qualifying international interns in Singapore.
- Meaningful compute allocation, equipment, and research resources.
- Conference travel support if a paper is accepted.
Skills
Python, PyTorch, JAX, Diffusion Models, Flow-Based Models, Model Distillation, Reinforcement Learning, Preference Optimization, Computer Vision, Generative Modeling, Multimodal Learning, Video Generation, Reward Modeling, Model Evaluation, Generative AI
Similar jobs
AI Research jobs
Improbable
Remote
Conduct applied research on AI agents, designing experiments and evaluation systems to improve reliability, context retention, and multi-step task completion. The role requires strong AI/ML research, engineering, experimental design, and communication skills.
AI Digest
Remote
Conduct research on long-horizon, multi-agent AI behavior by designing agent environments, analyzing large-scale data, and running experiments. The role requires strong research judgment, rapid execution, independence, and familiarity with current AI developments.
AI Digest
Remote
Build, optimize, and evaluate long-running and multi-agent AI systems, along with tools for monitoring and analyzing their real-world behavior. The role requires software engineering experience with coding agents, strong independence, and familiarity with current AI developments.
Vanta
Remote
Build Vanta’s organizational intelligence layer by shipping prototypes, internal tools, and AI agent workflows that make cross-source data useful to EPD, GTM, and other teams. The role requires recent hands-on LLM product work, independent problem scoping, and strong judgment around AI quality, reliability, cost, and latency.