Senior Product Designer, Token Factory

Amsterdam · Prague · Berlinsenior

Design & CreativeProduct DesignerProduct Product Designer

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Quick Summary

Key Responsibilities

Designing clear, scalable interfaces for core end-to-end AI workflows: model selection and comparison, deployment and inference, inference observability and analysis, fine-tuning, dataset management,

Technical Tools

Design & CreativeProduct DesignerProduct Product Designer

Responsibilities

~1 min read

→Designing clear, scalable interfaces for core end-to-end AI workflows: model selection and comparison, deployment and inference, inference observability and analysis, fine-tuning, dataset management, batch inference, and agent configuration.
→Own the end-to-end design of services and features within the Nebius Token Factory, from discovery to delivery.
→Being ready to write high-quality interface copy — clear, precise text that helps users navigate complex scenarios and make informed decisions.
→Developing a deep understanding of how AI systems work under the hood, translating complex technical processes (fine-tuning, data pipelines, agent workflows) into clear and manageable user interfaces.
→Collaborating with product managers to formulate hypotheses, validate them with data and user feedback, and improve key product scenarios.
→Using modern AI tools as part of the design process across research, ideation, and prototyping stages (Figma Make, Cursor, lovable.dev, ChatGPT, Claude, etc.).
→Working closely with product, engineering, and ML teams — discussing, revisiting, and improving solutions based on feedback and shared understanding.
→Clearly present design solutions and rationale to cross-functional teams
→Contribute to the development and maintenance of the design system, ensuring consistency and quality across the product

5+ years of experience in product teams (SaaS / B2B / DevTools experience is a strong plus). Strong product thinking and the ability to turn complex processes into clear and transparent user journeys.
Experience working on technically complex products where understanding system logic and processes matters as much as UI. Ability to balance usability, consistency, and innovation in complex systems.
Willingness to dive into the AI domain: how datasets are prepared for fine-tuning, how fine-tuning works, how agents and their workflows are structured.
Openness to collaboration: ability to listen, argue constructively, and incorporate team feedback.
Interest in UX research and a clear understanding of its value for product decisions.