Machine Learning Engineer at Entain

Melbourne, Victoria, Australia -

Full Time

Start Date

Immediate

Expiry Date

02 Sep, 26

Salary

0.0

Posted On

04 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, TensorFlow, Scikit-learn, AWS, MLOps, CI/CD, Data Pipelines, Model Deployment, Real-time Inference, Personalisation, Recommendation Systems, Generative AI, Model Monitoring, Scalable ML Systems, Cloud-based ML Tooling

Industry

Entertainment Providers

Description

Who We Are Entain Australia & New Zealand is fearlessly transforming the racing, sports, and entertainment landscape - reimagining how customers experience their favourite brands. As part of a global powerhouse operating in over 40 countries with nearly 30,000 people, we’re home to leading ANZ names like Ladbrokes, Neds, TAB, and Betcha. Across Entain ANZ, we’re shaping the future of sport and gaming entertainment through creative innovation, storytelling, and technology - creating experiences that connect with millions of fans. Your Impact This is where AI meets real-world scale. As a Machine Learning Engineer at Entain, you’ll build and deploy intelligent systems that power personalisation, optimise operations, and enhance how millions of customers engage with our products across ANZ. You’ll work across the full ML lifecycle - from experimentation to production - turning complex data into high-impact, scalable solutions. Your work won’t sit in notebooks; it will directly influence customer experience and business performance. If you’re driven by solving meaningful problems and seeing your models make a measurable difference, this is your game. A Day in the Life Expect variety, ownership, and real impact. Monitor and improve live models, analysing performance, drift, and outcomes Partner with product and engineering teams to identify high-value ML opportunities Build and deploy models, feature pipelines, and real-time inference services Strengthen MLOps practices, improving deployment speed, reliability, and observability Collaborate with data scientists and engineers to take ideas from concept to production Contribute to architecture decisions and continuously raise the bar on ML engineering standards Your Strengths Proven experience deploying machine learning models into production Strong Python skills and hands-on experience with frameworks like PyTorch, TensorFlow, or Scikit-learn Solid understanding of data pipelines and scalable ML systems Experience with AWS and modern cloud-based ML tooling Strong grasp of MLOps, CI/CD, monitoring, and model lifecycle management Comfortable working with large datasets and production systems A balance of experimentation and engineering rigour Clear communicator who can influence both technical and non-technical stakeholders Curious, proactive, and motivated to build systems that deliver real impact Experience in personalisation, recommendation systems or generative AI is a strong plus. Life at Entain At Entain, it’s more than a job - it’s a place to grow, connect, and make an impact. We value individuality, celebrate collaboration, and create space for bold ideas that move people. Here, you’ll help shape the voice of some of Australia and New Zealand’s most recognised brands - while developing your own craft in a supportive, ambitious team. Perks You’ll Love Hybrid & Flexible: Balance your life and work. Recognition & Rewards: Celebrate wins and enjoy retailer discounts. Wellbeing Perks: Support for your health and happiness. Entain, there’s nothing like it. For more information, please reach out to us at careers@entaingroup.com.au or hit apply now.

Responsibilities

Build and deploy scalable machine learning systems to power personalisation and optimise operations across ANZ products. Manage the full ML lifecycle from experimentation to production, including the development of feature pipelines and MLOps practices.