Published on
May 19, 2025
Data Scientist
Data Scientist
GPU Benchmarking & Hardware Optimization
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 cluster from scratch. If you've ever wanted to help shape a cloud platform from day one, this is your moment.
The Role
We’re looking for a data scientist with a strong understanding of GPU performance and modelling to help guide our hardware allocation strategy. This isn’t just about running benchmarks — it’s about developing intelligent, adaptive systems that learn from usage patterns and inform how we assign compute. You’ll design and execute GPU performance benchmarks, develop models that predict job
behaviour, and help us build tools that make smarter infrastructure decisions — all in a hands-on, startup environment.
What You’ll Do
Design and run GPU benchmarks across diverse models and workloads
Build predictive models for job performance and hardware suitability
Analyse job traces and runtime metrics to identify patterns and inefficiencies
Develop tooling for automated hardware configuration recommendations
Collaborate with engineering to integrate models into the orchestration layer
What We’re Looking For
Strong background in data science, applied ML, or systems modelling
Solid understanding of GPU architectures and compute stack (CUDA, PyTorch, etc.)
Experience designing experiments, benchmarking, and performance profiling
A highly creative and independent mindset — this is uncharted territory
Strong programming skills (Python preferred)
A sense of ownership and the drive to build practical systems from scratch
Bonus Points
Prior work in HPC, GPU scheduling, or performance modelling
Knowledge of compiler/runtime internals or low-level hardware profiling
Experience with ML-based or statistical workload prediction
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!
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 cluster from scratch. If you've ever wanted to help shape a cloud platform from day one, this is your moment.
The Role
We’re looking for a data scientist with a strong understanding of GPU performance and modelling to help guide our hardware allocation strategy. This isn’t just about running benchmarks — it’s about developing intelligent, adaptive systems that learn from usage patterns and inform how we assign compute. You’ll design and execute GPU performance benchmarks, develop models that predict job
behaviour, and help us build tools that make smarter infrastructure decisions — all in a hands-on, startup environment.
What You’ll Do
Design and run GPU benchmarks across diverse models and workloads
Build predictive models for job performance and hardware suitability
Analyse job traces and runtime metrics to identify patterns and inefficiencies
Develop tooling for automated hardware configuration recommendations
Collaborate with engineering to integrate models into the orchestration layer
What We’re Looking For
Strong background in data science, applied ML, or systems modelling
Solid understanding of GPU architectures and compute stack (CUDA, PyTorch, etc.)
Experience designing experiments, benchmarking, and performance profiling
A highly creative and independent mindset — this is uncharted territory
Strong programming skills (Python preferred)
A sense of ownership and the drive to build practical systems from scratch
Bonus Points
Prior work in HPC, GPU scheduling, or performance modelling
Knowledge of compiler/runtime internals or low-level hardware profiling
Experience with ML-based or statistical workload prediction
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. 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.