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Aristocrat Leisure

Global casino gaming content and platforms

ML Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBarcelona, SpainNo salary listed

About the Job

Requirements

  • At least 4 years of experience applying machine learning to real-world problems from data through deployment.
  • Proven experience applying recommender systems, such as collaborative filtering or ranking, to real products.
  • Strong Python skills and hands-on experience with machine-learning libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, or similar.
  • Solid SQL expertise and experience working with large data warehouses.
  • Hands-on experience with experiment-tracking and/or model-registry tools such as MLflow, Weights & Biases, or equivalent.
  • Experience designing or contributing to model monitoring or performance tracking in production.
  • Comfort working with cloud platforms such as GCP, AWS, or Azure, Docker, and Airflow.
  • A strong analytical foundation, with a background in a quantitative field such as mathematics, physics, computer science, or engineering, or equivalent experience.

Responsibilities

  • Design, train, evaluate, and retrain machine-learning models, especially recommender systems, to support game features, player experience, and operational efficiency.
  • Own the design of model-performance monitoring by defining tracked metrics such as drift, data quality, and degradation, setting thresholds, and determining model health in business terms.
  • Help establish an experimentation culture through model versioning and experiment tracking, making experiments reproducible and model versions easy to compare and promote.
  • Help establish model governance by defining how models are promoted to production and laying the foundation for communication between the MLOps team and Data Science.
  • Create templates and cookiecutter scaffolding to standardize 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 projects involving large language models, retrieval-augmented generation, and agentic artificial intelligence where they add value as a complement to the core role.
  • Develop simple interfaces such as Streamlit applications to expose machine-learning capabilities to non-technical users when useful.
  • Collaborate with product, data, and engineering teams, and communicate results, limitations, and recommendations to technical and business audiences.

Desired Qualifications

  • Experience with Snowflake or similar cloud data warehouses.
  • Hands-on experience building generative-artificial-intelligence applications using large language models, including API integration.
  • Interest or early experience in retrieval-augmented-generation systems through prototypes, side projects, or professional work.
  • Interest or familiarity with agentic artificial-intelligence concepts or frameworks such as LangChain agents or CrewAI.
  • Ability to build simple user interfaces such as Streamlit applications to expose machine-learning models to wider teams.

About the Company

Aristocrat Leisure

Global casino gaming content and platforms

Aristocrat Leisure is a global technology-powered entertainment company that creates casino and mobile gaming content. Its products include electronic gaming machines, casino management systems, free-to-play mobile games, and real-money online games across three units: Aristocrat Gaming, Product Madness, and Aristocrat Interactive. They differentiate themselves with a diversified portfolio spanning land-based, social, and online gaming, plus large game and platform ecosystems and a strong focus on responsible gameplay and staff development. Their goal is to deliver long-term value for stakeholders by providing high-quality gaming content while prioritizing player safety and responsible play.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
1953

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