Senior Machine Learning Engineer

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 Marketing Intelligence team, you will build the systems and infrastructure that power machine learning across DraftKings’ Casino, Sportsbook, and Fantasy verticals. Rather than focusing on a single model or use case, you will enable entire portfolios of models by designing scalable, reliable platforms for feature engineering, model deployment, and production workflows. You’ll work closely with Data Science, Engineering, and Product teams to reduce duplication, accelerate time-to-production, and raise the overall quality of machine learning systems. This role blends distributed data engineering, ML system design, and technical leadership in a high-impact, fast-paced environment.

• Lead the design and development of scalable ML infrastructure and data pipelines that support multiple Data Science teams across Marketing Intelligence
• Build reusable frameworks and workflows for feature engineering, model training, deployment, and backfilling at scale
• Design and maintain CI/CD systems for data and ML pipelines, enabling reliable and automated production deployments
• Improve system reliability through monitoring, alerting, and observability across data and ML workflows
• Partner with Data Scientists to productionize models, standardize workflows, and eliminate redundant engineering effort
• Optimize large-scale data processing workflows (e.g., Spark) for performance, cost, and reliability
• Drive improvements in developer experience through better abstractions, tooling, and shared patterns
• Mentor engineers and contribute to raising the team’s standards for system design, code quality, and operational excellence

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field
• Strong Python and SQL skills, with hands-on experience in distributed data processing (e.g., Spark)
• Experience designing and maintaining data/ML pipelines and orchestration workflows in production environments
• Experience with CI/CD for data or ML systems, including testing, deployment, and release management
• Experience working with cloud-based data platforms such as Databricks, Snowflake, or AWS (open to equivalent experience)
• Strong understanding of system design tradeoffs, including scalability, reliability, and maintainability
• Proven ability to deliver end-to-end solutions and operate them in production with a high sense of ownership
• Strong communication and collaboration skills, with experience working across Data Science and Engineering teams