Описание:
Aristocrat develops content and technology for the gaming industry and publishes free-to-play mobile games. Its business units cover regulated land-based gaming, social casino, and regulated real-money online gaming.
Задачи:
Design, train, evaluate, and retrain Machine Learning models, especially recommendation systems, to support game features, improve player experience, and optimize operational efficiency; Lead the design of model performance monitoring by defining metrics and aspects to track, setting thresholds, and determining model reliability from a business perspective; Establish experimentation practices through model versioning and experiment tracking with tools such as MLflow or Weights & Biases, ensuring reproducibility and easy comparison and promotion of model versions; Contribute to model governance practices by defining how models are promoted to production and establishing communication and collaboration processes between MLOps and Data Science teams; Create reusable templates and structures, such as Cookiecutter,



to standardize how the Data Science team structures, delivers, and communicates models and experiments; Build robust training and feature engineering pipelines and develop clean, production-ready Python and SQL code; Explore and contribute to early-stage projects involving LLMs, RAG, and Agentic AI when they add value; these are complementary to the role, not its primary responsibility; Develop simple interfaces, such as with Streamlit, to make Machine Learning capabilities accessible to non-technical users when useful; Collaborate with Product, Data, and Engineering teams, clearly communicating results, limitations, and recommendations to technical and business audiences.
Требования:
More than 4 years of experience applying Machine Learning to real-world problems, from data processing through model deployment; Demonstrated experience with recommendation systems, such as collaborative filtering, ranking, or similar techniques, ap

📌 ml engineer for social casino games (España)
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