GlobalFoundries is looking to integrate AI/ML solutions across its business, manufacturing, and enterprise functions to improve processes and drive innovation.
Requirements
- Proven experience integrating AI solutions into enterprise systems and business processes.
- Strong understanding of AI/ML lifecycle, from model development to production deployment and monitoring.
- Experience with cloud platforms (e.g., Azure, AWS) and AI/ML Ops tools.
- Familiarity with industrial AI use cases (e.g., predictive maintenance, process control, defect detection).
Responsibilities
- Partner with data science, platform, and engineering teams to ensure scalable architecture, deployment, and integration of AI/ML models into operational systems.
- Establish governance frameworks, performance KPIs, and feedback loops to monitor effectiveness and continuously refine AI deployments.
- Drive vendor and partner evaluations where third-party solutions are needed.
- Lead enterprise-wide AI integration initiatives aligned to business priorities (e.g., yield optimization, supply chain forecasting, workforce intelligence, customer support automation).
- Collaborate with business unit and functional leaders to identify high-impact use cases, shape solution requirements, and define measurable outcomes.
- Champion change management and user adoption strategies to drive behavioral and process shifts across functions.
- Act as a thought leader for AI enablement across GlobalFoundries, fostering a data-driven, innovation-focused culture.
Other
- 10+ years of experience in technology or digital transformation roles, with 4+ years leading AI/ML initiatives.
- Ability to manage cross-functional programs, influence senior stakeholders, and drive execution in a complex matrixed organization.
- Excellent communication and storytelling skills to translate technical concepts for business audiences.
- Experience in the semiconductor, advanced manufacturing, or high-tech industries.
- Bachelor’s degree in Computer Science , Engineering, Data Science, or related field.
