Asks for

The ad says“Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Strong software and systems engineering foundations, with a clear background in engineering or Computer Science.”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“Solid Python skills and comfort operating production services and their observability stack (e.g., Prometheus, Grafana).”
The ad says“Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).”
The ad says“Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).”
The ad says“4+ years in ML infrastructure, ML platform, or MLOps roles, ideally having worked inside a dedicated MLOps or platform team.”
The ad says“4+ years in ML infrastructure, ML platform, or MLOps roles, ideally having worked inside a dedicated MLOps or platform team.”
The ad says“Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).”
The ad says“4+ years in ML infrastructure, ML platform, or MLOps roles, ideally having worked inside a dedicated MLOps or platform team.”
The ad says“Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).”
The ad says“Solid Python skills and comfort operating production services and their observability stack (e.g., Prometheus, Grafana).”
The ad says“Solid Python skills and comfort operating production services and their observability stack (e.g., Prometheus, Grafana).”
The ad says“Strong software and systems engineering foundations, with a clear background in engineering or Computer Science.”
The ad says“Strong software and systems engineering foundations, with a clear background in engineering or Computer Science.”
The ad says“Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).”

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 MLOps Engineer to join our MLOps team and build and own the platform that takes our machine learning and AI systems reliably to production. You will focus on serving models as performant, real-time services, on the CI/CD and infrastructure around them, and on the tooling that lets our ML Engineers and Data Scientists ship, track and monitor models with confidence. You will make a real difference in our products and players' experiences.

What You'll Do

Deploy machine learning models as reliable, real-time APIs, with a strong focus on latency, throughput, caching, and scaling.
Design and own the serving and deployment infrastructure: containers, orchestration (Kubernetes), and serving frameworks (e.g., KServe, Triton, BentoML) where appropriate.
Build and maintain CI/CD pipelines for models, and orchestrate training and retraining workflows (e.g., Airflow).
Own the platform side of experiment tracking and model registry: versioning, lineage, promotion, and governance, so model releases are controlled and reproducible.
Build the monitoring and observability infrastructure that ML Engineers use to track model and system health (metrics, logging, tracing, alerting).
Ensure reproducibility across environments and pipelines, and harden systems for reliability (retries, timeouts, graceful degradation, rollback).
Partner with ML Engineers and Data Scientists to smooth the path from prototype to production, and with engineering on deeper system-design questions.

What We're Looking For

4+ years in ML infrastructure, ML platform, or MLOps roles, ideally having worked inside a dedicated MLOps or platform team.
Strong software and systems engineering foundations, with a clear background in engineering or Computer Science.
Proven experience serving models as real-time, low-latency services, with a solid grasp of caching, concurrency, and application performance (p95/p99).
Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms (e.g., GCP, AWS, Azure).
Experience with workflow orchestration (Airflow, Prefect, Kubeflow, or similar) and with experiment tracking / model registry tooling (MLflow, Weights & Biases).
Solid Python skills and comfort operating production services and their observability stack (e.g., Prometheus, Grafana).

Nice to Have

Experience with Snowflake or similar cloud data warehouses.
Experience supporting GenAI/LLM applications in production (serving, evaluation infrastructure, vector databases).
Exposure to designing AIOps-oriented infrastructure.
Interest in the ML/modeling side, enough to collaborate closely with ML Engineers (you do not need to be a researcher).

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 bring joy to life through the power of 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.