ML Engineer: AI for Gaming & LLM Innovations

Aristocrat Gaming; Barcelona; Presencial; EUR 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Robust benefits package

Global career opportunities

Descripción de la vacante

Aristocrat Gaming is seeking an ambitious ML/AI Engineer to advance our gaming technology. You will deploy models that power game features, player experiences, and operational efficiency, and refine data pipelines with Python and SQL.

You will explore LLMs, RAG, and agentic AI, build Streamlit interfaces for non-technical users, implement model monitoring, and collaborate with product, data, and engineering teams to maximize value.

Formación

• 5+ years of experience applying machine learning to real-world problems.
• Strong Python skills and hands‑on experience with ML Python libraries.
• Solid SQL expertise and experience working with large data warehouses.
• Comfort with cloud platforms (GCP, AWS, Azure), Docker, and Airflow.
• Ability to build simple user interfaces (e.g., Streamlit) to expose ML models to wider teams.
• Hands‑on experience building applications with Generative AI (LLMs), including API integration.
• Interest or early experience in RAG systems or agentic AI concepts.
• Degree in a relevant technical field or equivalent experience.

Responsabilidades

• Deploy machine learning models that support game features and player experience.
• Refine SQL and Python scripts for data transformation and modelling pipelines.
• Explore early-stage AI projects involving LLMs, RAG, and agentic AI.
• Develop or refine Streamlit-based tools to present ML capabilities to non-technical users.
• Build model monitoring systems to ensure long-term performance.

Conocimientos

Python

ML/AI

SQL

Cloud platforms

Educación

Degree in a relevant technical field

Herramientas

Docker

Airflow

Streamlit

LangChain

Descripción del empleo

Aristocrat Gaming is seeking an ambitious ML/AI Engineer to advance our gaming technology. You will deploy models that power game features, player experiences, and operational efficiency, and refine data pipelines with Python and SQL.

You will explore LLMs, RAG, and agentic AI, build Streamlit interfaces for non-technical users, implement model monitoring, and collaborate with product, data, and engineering teams to maximize value.