Role overview

Senior Machine Learning Engineer, Personalization

Requirements and responsibilities

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What You'll Do

  • 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 optimization.
  • 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.

What You'll Bring

  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field.
  • At least 3 years of experience working with machine learning systems in production environments.
  • Strong proficiency in Python and SQL, with experience working on distributed data platforms such as Spark.
  • Proven experience delivering production-grade machine learning models that drive measurable business impact.
  • Hands-on experience with Databricks for managing machine learning workflows, model lifecycle, and collaborative development.
  • Experience designing experiments and analyzing A/B tests to validate and optimize model performance.
  • Strong communication and collaboration skills, with experience mentoring or leading technical initiatives.
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackCI/CD, Python, SparkPrimary skills
Location1 accepted countryEligibility

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