Your mission
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
Your profile
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
Why us?
- 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
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