Junior AI & Knowledge Engineer

Randstad Digital

Zürich

Vor Ort

CHF 36.000 - 47.000

Teilzeit

vor 16 Stunden
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Zusammenfassung

Randstad Digital is seeking a Junior AI & Knowledge Engineer in Zurich. The role targets a Master student to support strategic AI and knowledge management initiatives within a global biopharma setting.

You will contribute to the AI Academy, Data Academy, Knowledge Navigator and related AI-enabled knowledge solutions. Ideal for someone who enjoys knowledge graph design, information architecture and user-centric digital product design.

Qualifikationen

  • Master student enrolled at ETH Zürich in CS/DS/Info Systems or related field.
  • Experience with Generative AI and AI tools in real workloads recommended.
  • Familiar with knowledge graphs, taxonomies and metadata modelling.
  • Proficiency in SharePoint Online and Microsoft 365 is a plus.
  • Comfort with UX/UI concepts and data visualization is beneficial.

Aufgaben

  • Support design of learning pathways, curricula and bootcamp concepts.
  • Develop learning materials, templates and academy content.
  • Research AI tools and translate use cases into training examples.
  • Create AI use case catalogues, prompts and demonstrations for knowledge work.
  • Assist with stakeholder communications and executive summaries.

Kenntnisse

Generative AI usage
Knowledge graphs
RAG architectures
UX/UI design
Python
Data visualisation
Graph database concepts

Ausbildung

Master student in Computer Science at ETH Zürich

Tools

Microsoft Copilot
Cowork
SharePoint Online
Microsoft 365

Jobbeschreibung

A leading pharmaceutical company is looking for a Junior AI & Knowledge Engineer based in Zurich, Switzerland

Duration: 2-4 months

Language: English/ German an advantage

Role overview

We are looking for a highly motivated Master student to support strategic AI and Knowledge

Management initiatives within a global biopharmaceutical environment. The role will work closely with

the MSAT Knowledge Management Lead and contribute to the design and deployment of the AI Academy,

Data Academy, Process Wiki / Knowledge Navigator, and related AI-enabled knowledge solutions.

The assignment is ideal for a student who enjoys building at the intersection of AI tools, knowledge

management, knowledge graph design, information architecture, and user-centric digital product design.

Key responsibilities (depending which workstream assigned to)
  • Support the design of learning pathways, training curricula, capability frameworks and bootcamp concepts.
  • Develop practical learning & workshop materials, exercise templates and reusable academy content.
  • Research emerging AI tools and translate relevant use cases into MSAT-oriented training examples.
  • Create AI use case catalogues, prompt examples and practical demonstrations for knowledge work, data work and process intelligence.
  • Support launch communication, stakeholder updates and executive-ready summaries.
Process Wiki / Knowledge Navigator
  • Support the design of a modern digital knowledge infrastructure for process knowledge, process data
  • and modelling-related content.
  • Create intuitive navigation structures & page concepts
  • Develop page mock-ups, wireframes and proof-of-concept knowledge portal designs.
  • Improve discoverability through taxonomy, metadata and search-oriented content structuring.
  • Contribute to the integration concept for multiple knowledge sources into a unified knowledge navigator
  • experience.
AI tools, knowledge graphs and agentic knowledge solutions
  • Apply AI productivity tools such as Microsoft Copilot, Cowork or comparable AI assistant platforms to accelerate content creation, knowledge structuring and prototyping.
  • Support conceptual knowledge graph design by defining entities, relationships and metadata patterns
  • Evaluate approaches for semantic search, retrieval-augmented generation and AI-assisted knowledge
  • retrieval.
  • Contribute to concepts for Copilot / Cowork-based assistants, process wiki agents and AI-enabled
  • knowledge workflows.
  • Document design decisions, assumptions and recommendations in a structured and reusable way.
Web page creation, UX and visual design
  • Design clean, user-friendly web pages and knowledge portal layouts.
  • Apply principles of information architecture, UX/UI design and visual storytelling.
  • Create clickable prototypes or lightweight demonstrators where appropriate.
  • Support SharePoint Online page design and modern web content structuring.
  • Translate complex knowledge and data concepts into accessible, visually clear user experiences.
Required qualifications

Education. Currently enrolled in a Master programme at ETH Zürich preferably in the field of Computer Science, Data Science, Information Systems, Computational Science, Knowledge Engineering, Digital Design or a related field.

Technical experience. Practical experience in several of the following areas is recommended:

  • Generative AI and large language model usage in real work scenarios.
  • Microsoft Copilot, Cowork or comparable AI assistant / agent platforms.
  • Knowledge graphs, semantic models, taxonomies or metadata modelling.
  • RAG architectures, semantic search or AI-enabled knowledge retrieval.
  • SharePoint Online, Microsoft 365 or enterprise collaboration platforms.
  • UX/UI design, wireframing and user journey development.
  • Python, data visualisation or graph database concepts are a plus.
Personal profile
  • Curious about the future of AI, knowledge management and digital transformation.
  • Able to structure ambiguous topics and translate them into executable work packages.
  • Comfortable working independently while aligning frequently with stakeholders.
  • Strong visual communication and storytelling skills.
  • Interest in biopharmaceutical manufacturing, process intelligence and enterprise knowledge systems.
  • High attention to detail, with the ability to make complex knowledge accessible and easy to reuse.
Expected deliverables (depending which workstream assigned to)
Workstream Expected contribution
AI Academy and Data & Modelling Academy
  • content structure, learning pathways, workshop
  • concepts and reusable training assets.
Knowledge product
  • Process Wiki / Knowledge Navigator MVP concept,
  • navigation model, page design prototypes and
  • AI & knowledge engineering
  • Knowledge graph concept, taxonomy and
  • search options and AI-agent integration ideas.
Communication assets
  • Executive-ready summaries, visual storylines,
  • stakeholder updates and working materials for
What the student will gain
  • Hands-on experience in enterprise AI transformation and AI-enabled knowledge management.
  • Exposure to strategic academy development, capability building and community enablement.
  • Opportunity to work on a visible Process Wiki / Knowledge Navigator MVP with real business impact.
  • Experience with modern AI tools, knowledge graph concepts and digital product design in a regulated
  • Close collaboration with experts in MSAT, Process Intelligence, Knowledge Management, Digital & Data
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