Staff Engineer - Recommendations & Personalization Systems

Triwill Group

France

Sur place

EUR 95 000 - 130 000

Plein temps

14 jours+

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Résumé du poste

Triwill Group, listed through our partner, seeks a Staff Engineer - Recommendations in France to advance personalized content recommendations across the platform. You will design systems to process large volumes of user data, APIs, and ML-enabled features, spanning data engineering, backend development, and personalization.

Collaborate with data scientists, product managers, and engineers to translate behavioral signals into meaningful experiences, improving relevance across content,

Qualifications

  • This position is listed on behalf of a partner company, who manages all applications and next steps.
  • Staff Engineer - Recommendations based in France.
  • Help evolve recommendation systems that connect users with relevant content, communities, groups, and events.
  • Collaborate with data scientists, product managers, and engineers to turn behavioral signals into meaningful user experiences.
  • The role involves data engineering, backend development, and personalization across cloud infrastructure, data pipelines, APIs, distributed systems, and ML-enabled applications.
  • Advance personalization from simple heuristics toward data-driven recommendations.

Responsabilités

  • Design systems capable of processing large volumes of platform-generated data.
  • Collaborate with data scientists, product managers, and engineers to translate insights into user experiences.

Description du poste

Triwill Group, listed through our partner, seeks a Staff Engineer - Recommendations in France to advance personalized content recommendations across the platform. You will design systems to process large volumes of user data, APIs, and ML-enabled features, spanning data engineering, backend development, and personalization.

Collaborate with data scientists, product managers, and engineers to translate behavioral signals into meaningful experiences, improving relevance across content,

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