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 design and run experiments that make training and inference faster, cheaper, and more reliable. You’ll publish clear benchmarks and feed signals back into the product.

What we are working on

• Benchmarks across model classes (LLMs, vision, multimodal)
• Throughput/latency optimization and stability under scale
• Runtime estimation signals and scheduling heuristics
• Reference pipelines and evaluation suites
• Practical guidance: docs, recipes, baselines

What We’re Looking For

• Enrollment in CS, Engineering, Physics/Math, or similar (or equivalent experience)
• Strong fundamentals in model training and evaluation
• Clear writing; reproducible results
• Tech stack: Python, PyTorch/JAX (and/or TensorFlow). CUDA/GPU literacy is a plus.

Bonus Points

• Large-scale training, distributed setups, mixed precision
• Dataset curation, eval design, reproducibility practice
• Publications, open-source work, well-documented artifacts

Why Join Us

• Learn fast: Get exposure to cutting-edge GPU infrastructure and real ML workloads
• Real impact: Contribute to features, guides, and benchmarks that users rely on
• Early-stage experience: See how product, engineering, and customer feedback come together in a startup
• Mentorship & growth: Work closely with experienced engineers and scientists in AI infra

Lyceum is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.