ML Engineer

Reposted 5 Days Ago
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Barcelona, Cataluña, ESP
Hybrid
Mid level
Gaming • Internet of Things • Machine Learning • Software
We're bringing joy to life through the power of play.
The Role
Own machine learning models end to end, with emphasis on recommender systems, from data preparation and experimentation through production deployment. Design monitoring, experiment tracking, model governance, and feature-engineering pipelines. Build production-ready Python and SQL solutions, contribute to LLM, RAG, and agentic AI initiatives, and create simple interfaces for nontechnical users. Collaborate across product, data, and engineering teams to communicate results and recommendations.
Summary Generated by Built In

At Aristocrat, we are advancing gaming technology with modern, powerful solutions. Our mission is to bring happiness to life through play. We value collaboration, creativity, and a strong passion for excellence. These roles primarily support the Machine Learning area of our Product Madness business line — a tech company specialised in social casino mobile games. We are looking for an ML Engineer to join our MLOps team and strengthen its modeling core. You will own machine learning models end to end, from data and experimentation to production, and help us build the monitoring and experimentation culture that keeps them reliable and aligned with the business over time. You will make a real difference in our products and players' experiences.


What You'll Do
  • 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.

What We're Looking For
  • 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.

Why Aristocrat?

Aristocrat is a world leader in gaming content and technology, and a top-tier publisher of free-to-play mobile games. Aristocrat has three operating business units, spanning regulated land-based gaming (Aristocrat Gaming), social casino (Product Madness), and regulated online real-money gaming (Aristocrat Interactive). Our team of over 7,300 employees worldwide is united by our company’s mission to bring joy to life through the power of play.

We deliver great performance for our B2B customers and bring joy to the lives of the millions of people who love to play our casino and mobile games. And while we focus on fun, we never forget our responsibilities. We strive to lead the way in responsible gameplay, and to lift the bar in company governance, employee wellbeing and sustainability. We’re a diverse business united by shared values and an inspiring mission to brighten life through the joy found in play.

Travel Expectations - Minimal travel required (up to 5%)


Additional Information

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.

Compensation Philosophy

We offer a comprehensive pay and benefits package designed to stay competitive in the market, support your wellbeing, and recognise your contribution to our success. Our approach is underpinned by a pay-for-performance belief in rewarding individual impact. Your specific compensation package will be determined by factors such as your skills, experience, qualifications, and location.

Depending on your role and location, you may be eligible for annual bonuses and incentives, health and wellbeing benefits, paid time off, retirement plans, insurance coverage, and other local or statutory benefits.

Specific details about compensation and benefits for this position will be discussed during the recruitment process.

Skills Required

  • 4+ years of experience applying machine learning to real-world problems from data through deployment
  • Proven experience with recommender systems, collaborative filtering, ranking, or similar systems applied to real products
  • Strong Python skills and hands-on experience with machine learning 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 or model registry tools such as MLflow or Weights & Biases
  • Experience designing or contributing to production model monitoring and performance tracking
  • Experience with cloud platforms, Docker, and Airflow
  • Quantitative background in mathematics, physics, computer science, engineering, or equivalent experience
  • Experience with Snowflake or similar cloud data warehouses
  • Hands-on experience building generative AI applications with LLMs and API integration
  • Interest or experience with RAG systems
  • Interest or familiarity with agentic AI concepts or frameworks such as LangChain agents or CrewAI
  • Ability to build simple user interfaces such as Streamlit applications

Aristocrat Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Aristocrat and has not been reviewed or approved by Aristocrat.

  • Healthcare Strength — Health coverage is considered strong, with mentions of comprehensive medical, dental, and vision options plus mental‑health resources. Descriptions point to solid insurance offerings across core areas.
  • Retirement Support — Retirement benefits include a 401(k) with employer matching, positioned as a notable part of the package. This element is consistently referenced alongside other key benefits.
  • Parental & Family Support — Family support is emphasized through paid parental leave, adoption or surrogacy assistance, and benefits that can include dependents. Wellbeing resources are described as part of the broader family-support ecosystem.

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The Company
HQ: Las Vegas, NV
6,500 Employees

What We Do

Aristocrat Leisure Limited is an ASX20 listed company and one of the world’s leading providers of gaming solutions. We’re licensed in over 300 jurisdictions and operate in over 90 countries around the world. We’re also proud to have a team of over 6500 employees that deliver outstanding results by pushing the boundaries of innovation, creativity and technology each day. We offer a diverse range of products and services including electronic gaming machines, social gaming and casino management systems, but it doesn’t stop there. Despite our global presence and exponential growth, we remain an ideas company at heart that is committed to delivering outstanding results for our customers and players and an unparalleled experience for our employees, who have the opportunity to grow, be inspired and be the best they can be. Our values of Talent Unleashed, All About the Player, Collective Brilliance and Good Business, Good Citizen guide and inspire us to live our mission of bringing joy to life through the power of play – every day. Come and join us – let’s play!

Why Work With Us

Individually we’re great, but together we’re brilliant. Our employees are the beating heart of our business and we attract the best people in the industry thanks to our unique and inspiring culture. Come and join the team and help bring joy to life through the power of play.

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