Director, Decision Science AI/ML Engineering & Ops

Responsibilities

• Develop and execute a comprehensive MLOps roadmap to architect repeatable practices across a portfolio of projects.
• Lead and mentor a specialized team of AI/ML engineers to build scalable, automated pipelines and feature stores.
• Design and champion a library of reusable building blocks, such as feature engineering modules and model templates, to accelerate development cycles.
• Act as a technical translator between Science development teams and the DS Technology organization to ensure interoperability.
• Drive operational excellence by implementing automated testing, validation suites, and KPI dashboards for model reliability and data quality.
• Partner with Decision Science Delivery teams to co-design and engineer scalable batch and callable science services.
• Manage technical debt and ensure the stability, security, and modernization of existing production ML ecosystems.
• Champion Responsible AI principles, ensuring security, privacy, and explainability are embedded by design.

Requirements

• 12+ years of related experience in data science, machine learning, or engineering.
• Proven experience leading decision scientists or machine learning engineers to deploy production-scale solutions.
• Strong statistical and modeling fluency, with the ability to diagnose model drift and assess output integrity.
• Proficiency in analytical coding languages including Python, R, and SQL.
• Extensive experience with mathematical modeling approaches (supervised, unsupervised, reinforcement learning, optimization, etc.).
• Experience designing and implementing complex algorithms within performance and time-to-market constraints.
• Hands-on experience with software development tools such as GitLab/GitHub, Docker, and CI/CD practices.
• Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a comparable field.

Preferred Qualifications

• Experience with generative AI (genAI) capability development.
• Knowledge of cloud computing concepts, including auto-scaling and AWS infrastructure/services.
• Familiarity with emergent design patterns, such as agent-driven solutions and interactive LLM implementations.
• Master’s degree in Computer Science, Computer Engineering, or an MBA.

About the Company

The Walt Disney Company is a leading diversified international family entertainment and media enterprise. The Disney Decision Science and Integration (DDSI) team serves as the engine behind science-driven decision-making across the enterprise, leveraging advanced algorithms to shape business decisions for brands including Disney+, ESPN, and Disney Experiences.