TL;DR

Machine Learning Engineer, Marketplace (AI): Building and improving recommendation systems on Eneba's marketplace with an accent on user behaviour analysis, model design, and experimentation. Focus on deploying models that improve engagement and revenue, and working closely with product, engineering, and data platform teams.

Location: Remote

Salary: €55,000 - €70,000 a year

Company

Eneba is building an open, safe, and sustainable marketplace for gamers, supporting close to 20m+ active users.

What you will do

  • Analyse user behaviour data to identify high-value personalisation features.
  • Design, train, and iterate on recommendation models.
  • Build and maintain end-to-end training and serving pipelines.
  • Define and track evaluation metrics tied directly to business KPIs.
  • Run rigorous A/B tests to benchmark new approaches.
  • Own monitoring and observability of deployed models.

Requirements

  • Hands-on experience designing and shipping recommender systems.
  • End-to-end ML ownership experience.
  • Strong Python and MLOps fluency.
  • Good English level is required, proficiency is preferred.

Nice to have

  • Experience with real-time or streaming inference (Kafka, Flink) for session-based recommendations.
  • Familiarity with Databricks and/or Apache Spark for large-scale data processing.
  • Production experience with feature stores.
  • Knowledge of two-tower / embedding-based retrieval at scale.
  • Familiarity with bandit algorithms or reinforcement learning for online recommendation optimisation.
  • Strong business communication skills.

Culture & Benefits

  • Opportunity to join the Employee Stock Options program.
  • Opportunity to help scale a unique product.
  • Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.
  • Paid volunteering opportunities.
  • Work location of your choice: office, remote, opportunity to work and travel.
  • Personal and professional growth supported by well-defined feedback and promotion processes.

Hiring process

  • The company may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
  • Final hiring decisions are ultimately made by humans.