Senior Machine Learning Engineer, Personalization

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours 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 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.

• 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.