Описание:
Aristocrat develops gaming content and technology, including free-to-play mobile games, regulated land-based gaming, social casino games, and regulated online real-money gaming.
Задачи:
Design, train, evaluate, and retrain machine learning models, especially recommender systems, to support game features, player experience, and operational efficiency Own model performance monitoring design, including tracked metrics, thresholds, and business-based health criteria Establish experimentation practices through model versioning and experiment tracking with tools such as MLflow or Weights & Biases Establish model governance practices, define production promotion processes, and lay the foundations for communication between the MLOps team and Data Science Create templates and cookiecutter scaffolding to standardise how Data Science structures, hands off, and communicates models and experiments Build robust training and feature-engineering pipelines and write clean, production-ready Python and SQL Explore and contribute to early-stage LLM, RAG,



and agentic AI projects where they add value as a complement to the role Develop simple interfaces, such as Streamlit apps, to expose ML capabilities to non-technical users when useful Collaborate across product, data, and engineering teams and communicate results, limitations, and recommendations to technical and business audiences.
Требования:
4+ Years of experience applying machine learning to real-world problems, from data to deployment Proven experience with recommender systems, such as collaborative filtering or ranking, applied to real products Strong Python skills and hands-on experience with ML libraries such as scikit-learn, PyTorch/TensorFlow, or XGBoost Solid SQL expertise and experience working with large data warehouses Hands-on experience with experiment tracking and/or model registry tools such as MLflow or Weights & Biases Experience designing or contributing to production model monitoring or performance trac

📌 ml engineer in social casino games (Barcelona)
🏢 HireHi
📍 Barcelona