Senior Machine Learning Engineer, Personalization

As a Senior Machine Learning Engineer on the Personalization team, you'll shape how players experience our products by building real-time, one-to-one personalization at scale. You'll design and deploy machine learning systems that deepen engagement, improve retention, and drive long-term player value. Working across Engineering, Product, and Analytics teams, you'll turn data into impactful experiences while advancing how we build, deploy, and optimize ML solutions. This role blends hands-on model development with system design and technical leadership in a fast-moving, high-impact environment.

• Lead end-to-end machine learning initiatives focused on improving player engagement and retention, from initial concept through production deployment.
• Build scalable, reusable machine learning pipelines with a focus on reliability, maintainability, and performance.
• Design and manage CI/CD workflows for machine learning using tools like MLflow, Jenkins, and GitOps to enable automated and efficient model deployment.
• Monitor model performance in production, implementing retraining strategies, drift detection, and continuous optimisation.
• Partner with cross-functional teams to translate business goals and user insights into high-impact machine learning solutions.
• Mentor other engineers and help define best practices for machine learning system design, development, and deployment.

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field (required).
• At least 3 years of experience working with machine learning systems in production environments (required).
• Strong proficiency in Python and SQL, with experience working on distributed data platforms such as Spark (required).
• Proven experience delivering production-grade machine learning models that drive measurable business impact (required).
• Hands-on experience with Databricks for managing machine learning workflows, model lifecycle, and collaborative development (required).
• Experience designing experiments and analysing A/B tests to validate and optimise model performance (required).
• Strong communication and collaboration skills, with experience mentoring or leading technical initiatives (required).