Senior Principal, AI Product Owner - Machine Learning

Senior AI Product Owner — Machine Learning 

AI, Data & Digital Enablement — Global Supply Chain 

Here at Entegris, we use advanced science to enable technologies that transform the world, and we are seeking employees who have the drive to continue that mission. 

The Role: 

Entegris is seeking a Senior AI Product Owner — Machine Learning to join our Global Supply Chain organization in a remote, U.S.-based role. Within Global Supply Chain, the AI, Data & Digital Enablement team is building the data foundation, AI capabilities, and digital products that make our supply chain more predictive, resilient, and efficient. 

Reporting to the VP, AI and Data, you will own the strategy, roadmap, and delivery of predictive and prescriptive machine learning products that drive better decisions across the supply chain. This is a senior, builder-level role: you’ll shape the product portfolio, stand up the practice, establish governance and guardrails, and ensure the underlying data is AI-ready — partnering with business leaders, IT, data engineering, and data science to take solutions from concept to scaled production. 

What You’ll Do: 

Machine Learning Product Leadership 

• Be the domain expert and provide senior principal, consultant level approach for developing and maturing best practices.  Own the roadmap for ML products — demand and supply forecasting, inventory and network optimization, predictive quality and maintenance, yield, and risk scoring. 

• Partner with data science and ML engineering across the full lifecycle — problem framing, feature engineering, training, validation, deployment, and monitoring — with strong MLOps discipline (CI/CD, drift detection, retraining). 

• Champion feature stores, data contracts, and model documentation to make solutions reproducible and production-grade. 

• Translate model outputs into decisions and workflows that operations teams trust and adopt. 

Data Readiness for AI 

• Partner with data engineering and governance teams to assess and elevate the readiness of supply chain, manufacturing, quality, and operational data for AI — accuracy, completeness, lineage, timeliness, and accessibility. 

• Champion the data-quality standards, metadata, and master data your products depend on, and drive readiness assessments before solutions move to production. 

Building the Practice 

• Stand up and scale the capability within Entegris’ AI, Data & Digital Enablement function — reusable patterns, playbooks, reference architectures, and evaluation frameworks. 

• Mentor product owners and analysts, grow AI literacy, and cultivate a community of practice that lets delivery scale across the organization. 

Establishing Governance 

• Define and operationalize Responsible AI governance — risk, security, data and IP protection, model/solution oversight, audit trails, and compliance — aligned to Entegris policy and emerging AI regulation. 

• Set the guardrails and approval gates appropriate to a mission-critical operations environment. 

Value Creation 

• Build business cases, prioritize by ROI, and instrument value tracking against clear baselines (cost-to-serve, working capital, cycle time, quality, and service).