ML Research Intern – Runtime Prediction

ML Research Intern – Runtime PredictionAbout LyceumLyceum is building a user-centric GPU cloud from the ground up. Our mission is to make high-performance computing seamless, accessible, and tailored to the needs of modern AI and ML workloads. We're not just deploying infrastructure, we’re designing and building our own large-scale GPU clusters from scratch. If you've ever wanted to help shape a cloud platform from day one, this is your moment.The Role:You’ll join our R&D team as a junior researcher working on runtime prediction, hardware selection, and workload efficiency.You will support the design of experiments, help build models that predict resource requirements, and contribute to deploying them on our infrastructure to automate scheduling and cost prediction for customers. This role is ideal for a Master’s student, e.g. in the context of a thesis or research internship.What we are working onRuntime prediction models & scheduling heuristicsBenchmarking across LLMs, vision & multimodal modelsThroughput, latency & stability optimisation at scaleWorkload profiling (VRAM/compute/memory)Reference pipelines, reproducible evaluation suitesPractical docs, baselines, and performance guidanceWhat We’re Looking ForCurrently enrolled in a Master’s in CS/AI/ML (ideally working on or preparing a thesis in applied ML)Solid fundamentals in model training & evaluationFirst experience from research projects, a lab, or industry internships (Research Engineer/Assistant/Scientist)Interest in model efficiency or GPU performance (quantization, pruning, large-scale training, profiling)Ownership mindset and rigor in experimentation, even at junior levelClear writing; reproducible resultsBased in CH or open to relocating to Switzerland for the internshipTech stack: Python, PyTorch/JAX (and/or TensorFlow). CUDA/GPU literacy is a plus.Bonus PointsExperience with large-scale or distributed training (e.g. in a university or lab setting)Exposure to dataset curation, evaluation design, or reproducibility practicesPublications, thesis work, or high-quality open-source contributionsWhy Join UsBuild from zero: This is a rare opportunity to join a startup at the earliest stages and help shape not just the product, but the foundation of the company. You’ll have real ownership over your projects and the chance to grow into a full-time role.Hard, meaningful problems: We’re tackling some of the most interesting challenges in cloud infrastructure, scheduling, and performance optimization, at the intersection of hardware and AI.World-class hardware: You’ll be working directly with cutting-edge GPU hardware and helping build the most performant compute platforms in Europe.Everything else: Compensation, mentorship, team events etc – it’s our job to make sure you have everything you need to learn fast and do your best work!Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.