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 Masters and PhD students who are excited about multimodal intelligence and interested in working on challenging research problems with real-world large-scale AI systems.

Depending on your background research interests and experience you may contribute to one or more of the following areas:

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 & Memory

• 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

• Scalable AI infrastructure

AI for Real-World Applications

• 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

You will have the opportunity to 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 also be opportunities to publish research papers or contribute to open-source projects.

• Currently pursuing a Masters or PhD degree in Computer Science Electrical Engineering Artificial Intelligence Machine Learning or a related field

• Strong interest in Multimodal AI Generative AI LLMs Computer Vision Video or AI Systems

• Solid programming skills in Python and/or C

• Familiarity with PyTorch and modern deep learning frameworks

• Strong analytical problem-solving and research skills

• Ability and motivation to independently explore and prototype new ideas

Experience in one or more of the following areas would be an advantage:

• Vision-Language Models Video Generation or Diffusion Models

• LLM inference and optimization

• CUDA GPU or NPU programming

• Distributed training or inference

• Quantization sparsity or efficient attention

• Large-scale AI systems

• Open-source AI projects

• Academic research and publications

• The opportunity to work on cutting-edge Multimodal AI Video Generation World Models and AI Systems research

• Close collaboration with researchers and engineers from leading universities research institutions and industry teams

• Access to large-scale AI models and advanced AI computing platforms

• Opportunities to publish research and contribute to open-source projects

• A highly international research environment in Europe

• Potential opportunities for continued collaboration thesis projects or future positions

We are particularly interested in students who are not only excited about making AI models smarter but who also want to explore:

How can we make large multimodal models faster more scalable and more efficient

If you are excited about the future of Multimodal AI Video Generation World Models and large-scale AI Systems we would love to hear from you.