Senior Product Designer
Apheris Ai Gmbh Remote (đŠđŞ Berlin, Germany)
The Senior Product Designer will own the end-to-end UX and UI design across multiple scientific applications, focusing on usability for drug discovery scientists. This involves translating product strategy and user needs into effective designs, developing prototypes, and designing production-ready interfaces that balance scientific complexity with clarity.
Responsibilities
- Own the end-to-end UX and UI design across multiple Apheris products
- Work closely with the Product team and scientific stakeholders to translate product strategy, user needs, and technical constraints into effective design solutions
- Develop wireframes and quick prototypes to test concepts with external users and domain experts
- Design and refine production-ready interfaces that balance scientific complexity with clarity and ease of use
- Actively engage with users to understand their workflows and validate design decisions
Requirements
- Strong experience as a Product Designer
- User-first mindset
- Proven ability to move from low-fidelity concepts to polished, production-ready designs
- Experience using AI-powered prototyping tools
- Comfort working in fast-moving environments
- Strong communication skills
Benefits
- Industry-competitive compensation
- Remote-first working
- Great suite of benefits, including a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend and a learning and development budget
- Regular team lunches and social events
- Generous holiday allowance
- Office Days at our Berlin HQ or a different European location (3x a year)
Key Skills
About Apheris Ai Gmbh
Apheris delivers enterprise-grade AI applications for drug discovery, designed for pharma companies to run and customize securely within their own IT environments. By keeping all data local, organizations maintain full sovereignty over IP-sensitive assets. These local deployments also serve as the foundation for Apheris-hosted federated data networks, where pharma companies collaboratively train and benchmark models on proprietary datasets to unlock more robust and generalizable models for drug discovery.
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