Published on
Dec 16, 2025
ML Research Engineer - Runtime Prediction
Full-Time
Zurich / Berlin
About Lyceum
Lyceum 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 to work on runtime prediction, hardware selection, and workload efficiency.
You will design experiments, build models that predict resource requirements, and deploy them on our infrastructure to automate scheduling and cost prediction for customers.
What we are working on
Runtime prediction models & scheduling heuristics
Benchmarking across LLMs, vision & multimodal models
Throughput, latency & stability optimisation at scale
Workload profiling (VRAM/compute/memory)
Reference pipelines, reproducible evaluation suites
Practical docs, baselines, and performance guidance
What We’re Looking For
PhD in applied AI/ML OR Master’s in CS/AI/ML + 2+ years industry experience (Research Engineer/Scientist)
Strong fundamentals in model training & evaluation
Experience from a successful startup, big tech, or top research lab
Technical knowledge in model efficiency or GPU performance (quantization, pruning, large-scale training, profiling)
Ownership and rigor in experimentation
Clear writing; reproducible results
Based in CH or open to relocating to Switzerland
Tech stack: Python, PyTorch/JAX (and/or TensorFlow). CUDA/GPU literacy is a plus.
Bonus Points
Large-scale or distributed training experience
Dataset curation, evaluation design, reproducibility
Publications or high-quality open-source work
Why Join Us
Build from zero: This is a rare opportunity to join a startup at the earliest stages and shape not just the product, but the foundation of the company. You’ll have real ownership over what you build and the freedom to do things right from the beginning.
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, equity, healthcare, team events etc – it’s our job to make sure you have everything you need to do your thing!
Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
About Lyceum
Lyceum 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 to work on runtime prediction, hardware selection, and workload efficiency.
You will design experiments, build models that predict resource requirements, and deploy them on our infrastructure to automate scheduling and cost prediction for customers.
What we are working on
Runtime prediction models & scheduling heuristics
Benchmarking across LLMs, vision & multimodal models
Throughput, latency & stability optimisation at scale
Workload profiling (VRAM/compute/memory)
Reference pipelines, reproducible evaluation suites
Practical docs, baselines, and performance guidance
What We’re Looking For
PhD in applied AI/ML OR Master’s in CS/AI/ML + 2+ years industry experience (Research Engineer/Scientist)
Strong fundamentals in model training & evaluation
Experience from a successful startup, big tech, or top research lab
Technical knowledge in model efficiency or GPU performance (quantization, pruning, large-scale training, profiling)
Ownership and rigor in experimentation
Clear writing; reproducible results
Based in CH or open to relocating to Switzerland
Tech stack: Python, PyTorch/JAX (and/or TensorFlow). CUDA/GPU literacy is a plus.
Bonus Points
Large-scale or distributed training experience
Dataset curation, evaluation design, reproducibility
Publications or high-quality open-source work
Why Join Us
Build from zero: This is a rare opportunity to join a startup at the earliest stages and shape not just the product, but the foundation of the company. You’ll have real ownership over what you build and the freedom to do things right from the beginning.
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, equity, healthcare, team events etc – it’s our job to make sure you have everything you need to do your thing!
Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.