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Member of Technical Staff – AI Inference platform, features

lyceum · Zürich, Switzerland

Software DevelopmentImported listingfull-timeabout 1 hour ago

About The Role

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
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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.
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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.
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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
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Number of platform features shipped
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Time from customer request to feature availability
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Breadth of supported models, frameworks, and deployment configurations
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

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3+ years of experience in software engineering, with a focus on backend or infrastructure systems
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Strong proficiency in Go and Python
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Hands-on experience with at least one ML inference serving framework (vLLM, TGI, etc)
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Solid understanding of how large language models and other AI models are deployed and served in production
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Experience working with REST/gRPC APIs and designing developer-facing interfaces
Nice to have
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Familiarity with GPU scheduling, batching strategies, or inference optimisation (quantisation, speculative decoding, etc.)
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Experience with Kubernetes and container orchestration in a production setting
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Knowledge of AI model formats and conversion pipelines (GGUF, SafeTensors, ONNX)
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Background in developer tools, platform engineering, or API design
Why us?
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Outstanding team: Work with some of the best engineers in the world, coming from hedge funds, big tech, AI startups and top universities
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Once in a lifetime opportunity: Early-stage company in the fastest-growing market in the world
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Ownership: Shape how European AI companies access GPU compute
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European mission: Build sovereign, GDPR-compliant AI infrastructure for the next generation of deep-tech

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