Member of Technical Staff – AI Inference platform, features

You will expand the capabilities of Lyceum's AI inference platform, the first EU-sovereign inference cloud. You'll own the features that customers interact with directly: model serving configurations, API surface, framework integrations, and developer experience. This means understanding what customers need, building it fast, and making sure it works reliably at scale.

Your focus

- Feature development: Design and ship new platform capabilities - from supporting new model architectures and serving frameworks to building out API features that customers are asking for.

- Customer-facing engineering: Work closely with customers and the commercial team to understand real-world usage patterns, translate feature requests into technical designs, and iterate based on feedback.

- Developer experience: Improve the end-to-end experience of deploying and running inference on Lyceum, from initial setup through to monitoring and debugging in production.

Your KPIs

- Number of platform features shipped

- Time from customer request to feature availability

- Breadth of supported models, frameworks, and deployment configurations

- Customer feedback on platform usability and capability

We consider candidates from diverse backgrounds, with a deep love for technical challenges and the desire to take on ownership beyond what's reasonably expected. You're someone who stays close to the rapidly evolving open-source AI ecosystem and gets energy from turning emerging tools into production-grade platform capabilities.

Requirements

- 3+ years of experience in software engineering, with a focus on backend or infrastructure systems

- Strong proficiency in Go and Python

- Hands-on experience with at least one ML inference serving framework (vLLM, TGI, etc)

- Solid understanding of how large language models and other AI models are deployed and served in production

- Experience working with REST/gRPC APIs and designing developer-facing interfaces

Nice to have

- Familiarity with GPU scheduling, batching strategies, or inference optimisation (quantisation, speculative decoding, etc.)

- Experience with Kubernetes and container orchestration in a production setting

- Knowledge of AI model formats and conversion pipelines (GGUF, SafeTensors, ONNX)

- Background in developer tools, platform engineering, or API design

- Outstanding team: Work with some of the best engineers in the world, coming from hedge funds, big tech, AI startups and top universities.

- Once in a lifetime opportunity: Early-stage company in the fastest-growing market in the world

- Ownership: Shape how European AI companies access GPU compute

- European mission: Build sovereign, GDPR-compliant AI infrastructure for the next generation of deep-tech