Stage - Product Knowledge Content

TL;DR

Stage - Product Knowledge Content (Marketplace): Design and produce engaging training content across video, e-learning, and documentation formats with an accent on multimedia tools and knowledge management. Focus on structuring content for AI agents, identifying gaps through user engagement, and optimizing via analytics for better discoverability and impact.

Location: Bordeaux, France (onsite)

Company

Marketplace software leader founded in 2012 with 750+ employees in 9 offices worldwide, powering 450+ B2C/B2B marketplaces.

What you will do

• Design and produce content in video, e-learning, and written formats using tools like Guidde, Mindsmith, Veed, Paligo, and Confluence
• Structure and optimize content sources for Digital Agent, including architecture and metadata for self-service resolution
• Identify training needs and content gaps via internal/external engagement, proposing solutions for discoverability
• Use AI analytics to measure engagement, performance, and dynamically adapt materials
• Collaborate with Product, Technical, and Customer Success teams to keep content accurate and up-to-date

Requirements

• French: Native or fluent (required)
• English: B2 minimum (required)
• Pursuing degree in Communication, Content Design, Knowledge Management, Digital Learning, Technical Documentation, or related
• Strong organizational skills and ability to manage multiple projects
• Technical proficiency with multimedia/documentation tools; eagerness for AI technologies
• Understanding of content architecture and knowledge management
• Excellent communication and collaboration skills

Nice to have

• Experience in video production, multimedia creation, or technical documentation

Culture & Benefits

• Work hard together with teamwork and collaboration as foundation
• Prioritize action, efficiency, and going above & beyond for excellence
• Knowledge sharing and continuous learning core to culture
• Client success focus with diverse, ambitious, supportive colleagues

Hiring process

• CV screening + 10-min AI conversation with Emma (complete within 3 days)
• Intro call with recruiter
• Two interviews with manager Alice and colleagues using STAR method