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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Engineer - **Company:** Aristocrat Technologies - **Location:** Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Database, Python (Programming Language), Machine Learning, Recommender Systems, Tensorflow, Standard Sql, SQL Databases, Google Cloud, Feature Engineering, Pytorch, Large Language Models, Snowflake, Software Application Programming, Generative AI, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Virtual Agents, Streamlit Framework, Docker - **Published:** September 24, 2026 - **Apply:** https://startup.jobs/ml-engineer-aristocrat-technologies-indi-10156937 ## About the Role * 4+ years of experience applying machine learning to real-world problems, from data to deployment. * Proven experience with recommender systems (collaborative filtering, ranking, or similar) applied to real products. * Strong Python skills and hands-on experience with ML libraries (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 (MLflow, Weights & Biases, or equivalent). * Experience designing or contributing to model monitoring / performance tracking in production. * Comfort working with cloud platforms (e.g., GCP, AWS, Azure), Docker, and Airflow. * A strong analytical foundation, with a background in a quantitative field (mathematics, physics, computer science, engineering) or equivalent experience. Nice to Have * Experience with Snowflake or similar cloud data warehouses. * Hands-on experience building applications with Generative AI (LLMs), including API integration. * Interest or early experience in RAG systems - whether through prototypes, side projects, or professional work. * Interest or familiarity with agentic AI concepts or frameworks (e.g., LangChain agents, CrewAI). * Ability to build simple user interfaces (e.g., Streamlit) to expose ML models to wider teams. ## Description * Design, train, evaluate and retrain machine learning models - with emphasis on recommender systems - that support game features, player experience, and operational efficiency. * Own the design of our model performance monitoring: define what to track (drift, data quality, degradation), thresholds, and what "the model is still healthy" means in business terms. * Help establish a solid experimentation culture: model versioning and experiment tracking with tools such as MLflow or Weights & Biases, so experiments are reproducible and model versions are easy to compare and promote. * Help establish a model governance culture: define how models are promoted to production and lay the foundations of the communication contract between the MLOps team and Data Science. * Create templates and cookiecutter scaffolding to standardise how Data Science structures, hands off, and communicates its 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 LLMs, RAG and agentic AI where they bring value - as a complement to the role, not its core. * Develop simple interfaces (e.g., Streamlit) to expose ML capabilities to non-technical users when useful. * Collaborate with teams across product, data, and engineering, and communicate results, limitations, and recommendations clearly across technical and business audiences., Depending on the nature of your role, you may be required to register with the Nevada Gaming Control Board (NGCB) and/or other gaming jurisdictions in which we operate. This job description may have been reviewed and enhanced using AI-assisted tools to improve clarity, consistency, and inclusivity. All final content, role requirements and hiring decisions remain subject to human review and approval by Aristocrat. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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