Senior Principal, AI Product Owner - Machine Learning

Role Description

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:

• Shape the product portfolio.
• Stand up the practice.
• Establish governance and guardrails.
• Ensure the underlying data is AI-ready.
• Partner 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).
  • Report realized impact to supply chain and enterprise leadership, and continuously reprioritize the portfolio toward measurable outcomes.
• Stakeholder & Cross-Functional Leadership:
  • Run discovery with business owners, lead change management and adoption, and communicate progress, value, and risk to senior leadership.
  • Influence and align business, IT, data engineering, and data science partners around a shared roadmap.

Qualifications

• Strong command of the ML lifecycle and MLOps — feature engineering, training, validation, deployment, monitoring, and retraining.
• 15+ years in enterprise data, software development practices and/or product management/ownership, including 4+ years delivering AI/ML or data products, with a track record of taking solutions to scaled production.
• Demonstrated experience assessing and improving data readiness for AI — quality, lineage, metadata, and accessibility.
• Proven success building a new capability or practice and scaling it across an organization.
• Experience establishing AI governance, risk, and Responsible AI controls.
• Track record of value creation — connecting AI products to quantified business outcomes.
• Excellent stakeholder leadership and executive communication; able to influence senior business and technical leaders.
• Bachelor’s degree in a relevant field; advanced degree a plus.

Outstanding Candidates Will Have:

• Experience with ML platforms and Google Cloud Platform (GCP), including Vertex AI and BigQuery ML, is a plus.
• Experience in semiconductor, advanced materials, manufacturing, or global supply chain environments.
• Familiarity with enterprise platforms such as Microsoft Azure AI / Copilot, Databricks, SAP, and ServiceNow.
• Relevant certifications in product management, AI/ML, or cloud, and experience with Agile and modern product operating models.

Benefits

• Compensation: $175,000 - $230,000 per year range with actual pay dependent on candidate overall skills for the role.
• Generous 401(K) plan with an impressive employer match.
• Excellent health, dental and vision insurance packages to fit your needs.
• Flexible work schedule and 11 paid holidays a year.
• Paid time off (PTO) policy that empowers you to take the time you need to recharge.
• Education assistance to support your learning journey.
• Values-driven culture with colleagues that rally around People, Accountability, Creativity and Excellence.