Senior Machine Learning Engineer, Personalization

What You'll Do

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Lead end-to-end machine learning initiatives focused on improving player engagement and retention, from initial concept through production deployment.

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Build scalable, reusable machine learning pipelines with a focus on reliability, maintainability, and performance.

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Design and manage CI/CD workflows for machine learning using tools like MLflow, Jenkins, and GitOps to enable automated and efficient model deployment.

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Monitor model performance in production, implementing retraining strategies, drift detection, and continuous optimization.

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Partner with cross-functional teams to translate business goals and user insights into high-impact machine learning solutions.

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Mentor other engineers and help define best practices for machine learning system design, development, and deployment.

What You'll Bring

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Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field.

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At least 3 years of experience working with machine learning systems in production environments.

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Strong proficiency in Python and SQL, with experience working on distributed data platforms such as Spark.

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Proven experience delivering production-grade machine learning models that drive measurable business impact.

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Hands-on experience with Databricks for managing machine learning workflows, model lifecycle, and collaborative development.

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Experience designing experiments and analyzing A/B tests to validate and optimize model performance.

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Strong communication and collaboration skills, with experience mentoring or leading technical initiatives.