Multimodal AI & AI Systems Research Intern

We are a research team based in Europe, working at the intersection of Generative AI, Video, Efficient AI, and Distributed Systems. We collaborate closely with leading universities and research institutions, as well as engineering teams, to explore and build the next generation of efficient multimodal AI systems. We are looking for highly motivated Master’s and PhD students who are excited about multimodal intelligence and interested in working on challenging research problems with real-world, large-scale AI systems.

• Contribute to research in areas such as Multimodal & Generative AI, Vision-Language Models (VLMs), Video generation and understanding, World Models, Multimodal agents, Diffusion and generative models, Efficient AI, Model compression and quantization, Sparsity and efficient attention mechanisms, Inference optimization and acceleration, Efficient execution of large multimodal models, Long-context modeling, KV Cache optimization, Memory systems for large AI models, Efficient information retrieval and context management, AI Systems & Infrastructure, Distributed inference and parallel computing, Scheduling and resource optimization, GPU/NPU memory optimization, Hardware-software co-design, and Scalable AI infrastructure.
• Explore how large multimodal and generative models can be efficiently deployed in practical, large-scale scenarios.
• Develop and evaluate solutions that improve model performance, scalability, and efficiency.
• Identify interesting research problems, prototype new ideas, design and conduct experiments, and evaluate solutions at scale.
• Depending on the project and research outcomes, there may be opportunities to publish research papers or contribute to open-source projects.