Backend Engineer
Multimodal AI & AI Systems Research Intern
Zurich
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About The Team
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.
What You Will Work On
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
.
What We Are Looking For
- Currently pursuing a Master’s 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
What We Offer
- 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
Who We Are Looking For
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.
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