ML Engineer: AI for Gaming & LLM Innovations

Aristocrat Gaming

Barcelona

On-site

EUR 90,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Robust benefits package
Global career opportunities

Job summary

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.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

Python
ML/AI
SQL
Cloud platforms

Education

Degree in a relevant technical field

Tools

Docker
Airflow
Streamlit
LangChain

Job description

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.

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