Intern/Master Student — DC-OXC Traffic Scheduling for Super-Node Architecture

**Huawei Heisenberg Research Center (Munich)** is responsible for advanced technology research, architectural development, design and strategic engineering of our products. **The Optical Technology Laboratory** in Munich researches and develops signal processing, components, systems, and optical switching for fixed access, data center networks, metro and long-haul optical networks. The department engages in local research and collaborates with academic and industrial partners from the European ecosystem. Join us as a **Intern/Master Thesis Student — DC-OXC Traffic Scheduling for Super-Node Architecture** **(m/f/d)** **Your mission** * Study existing approaches to MoE traffic scheduling, collective communication optimization, and OCS-based interconnect architectures, build a clear understanding of how load imbalance in MoE inference leads to Alltoallv congestion and long-tail latency. * Research and implement techniques to transform random, dynamic sparse MoE traffic into deterministic, uniform traffic patterns that OCS can efficiently handle. * Investigate collective communication strategies that eliminate the need for frequent topology reconfiguration, leveraging optical path bandwidth to remove local hotspots and long-tail effects * Design and prototype load-aware routing algorithms that intelligently distribute non-uniform Token traffic across limited OCS "narrow pipes. * Develop software-level traffic smoothing mechanisms to eliminate physical-layer congestion jitter, targeting end-to-end inference latency equivalent to 100% load-balanced scenarios **Your areas of expertise** * Currently pursuing a Bachelor's, Master's degree in Computer Science, Computer Engineering, Electronic Engineering, Applied Mathematics, or a related field. * Solid understanding of deep learning fundamentals, including neural network architectures, training/inference pipelines, and GPU computation. * Strong background in graph theory, combinatorial optimization, linear/integer programming, or queuing theory. * Familiarity with multi-commodity flow optimization, network flow problems, or convex optimization is a strong plus. * Understanding of network interconnect technologies, including OCS (Optical Circuit Switching), InfiniBand, RoCE, or similar high-performance interconnects is a strong plus. * Basic understanding of MoE (Mixture of Experts) models — how Token routing works and why it creates non-uniform communication patterns. Deep expertise is not expected, but conceptual familiarity is required * Ability to work independently and collaboratively in a research-oriented environment * Fluent in written and spoken English language By applying to this position, you agree with our Recruitment Privacy Statement. You can read in full our privacy policy here. **Your rewards of working here** * Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network. * We offer healthy meals ranging from traditional Chinese to western delicacies in our famous company canteen. * To keep your development ongoing, you will find a broad range of training opportunities. Many online and face-to-face training programs incl. language courses in German and Mandarin. * Our diverse and welcoming environment is shaped by different backgrounds and around 40 individual nationalities. * Self-responsible work in a competent, motivated and constantly growing team. Please send your application and CV (incl. cover letter and reference letters) in English. **Huawei** is a leading global information and communications technology (ICT) solutions provider. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 208,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.