AI Site Lead – Manufacturing AI Transformation Engineer
STMicroelectronics · Calamba
OUR STORY
At STMicroelectronics, we believe in the power of technology to drive innovation and make a positive impact on people, businesses, and society. As a global semiconductor company, our advanced technologies and chips form the hidden foundation of the world we live in today.
When you join ST, you will be part of a global business with more than 122 nationalities, present in 40 countries, and comprising over 49,000 diverse and dedicated creators and makers of technology around the world.
Developing technologies takes more than talent: it takes amazing people who understand collaboration and respect. People with passion and the desire to disrupt the status quo, drive innovation, and unlock their own potential.
Embark on a journey with us, where you can innovate for a future that we want to make smarter and greener, in a responsible and sustainable way. Our technology starts with you.
Role Purpose
The AI Site Lead is responsible for driving AI transformation and value realization at the manufacturing site.
The role acts as the key interface between the site organization and the central Manufacturing Data Science / AI@BEM organization, translating manufacturing priorities and business challenges into a structured AI roadmap and executable project portfolio.
The AI Site Lead owns the site AI strategy, project pipeline, execution governance, adoption and business value realization, while coordinating the appropriate technical and domain resources required to deliver and scale AI solutions.
The position requires a strong combination of manufacturing experience, AI/data understanding, project leadership and cross-functional stakeholder management.
Key Responsibilities
1. Site AI Strategy & Roadmap
- Define and maintain the site's one to three (3-5) years AI roadmap aligned with Back End Manufacturing strategy and site business priorities.
- Identify manufacturing opportunities where AI and advanced analytics can improve quality, productivity, yield, equipment performance and operational efficiency.
- Build and continuously maintain the site AI project pipeline.
- Prioritize AI initiatives based on business impact, feasibility, resources and strategic importance.
- Translate manufacturing needs into clearly defined AI use cases and business requirements.
2. AI Portfolio & Project Delivery
- Own and govern the site-level AI portfolio from opportunity identification through deployment and adoption.
- Initiate and steer AI projects together with Domain Experts, Business Analysts, Project Managers, Data Scientists and Data Engineers.
- Ensure projects have clearly defined:
- Business objectives
- Project scope
- Expected value
- Technical and operational resources
- Milestones and deployment plan
- Identify project roadblocks and coordinate stakeholders to accelerate resolution.
- Support deployment, replication and scaling of successful AI solutions across the site.
- Drive increasing site self-sufficiency in executing AI projects, where appropriate.
3. Business Value Realization
- Be accountable for AI outcomes and value realization at site level.
- Establish business KPIs and value targets for AI initiatives.
- Track realized benefits including, where applicable:
- Yield improvement
- Quality improvement
- Productivity / UPH
- Scrap and cost reduction
- Equipment efficiency
- Downtime reduction
- Process optimization
- Ensure AI solutions move beyond PoC into production adoption and sustainable business impact.
- Drive replication and scaling of proven AI solutions.
4. Stakeholder & Resource Coordination
- Act as the primary AI focal point for the site.
- Build strong relationships with Site Management, Operations, Engineering, Quality, IT and other functions.
- Coordinate the site's AI resources and required competencies across projects.
- Bridge the site organization with the central Manufacturing Data Science / AI@BEM organization.
- Facilitate collaboration between manufacturing Domain Experts and technical AI teams.
- Ensure appropriate allocation and prioritization of resources across the AI portfolio.
5. AI Adoption & Capability Building
- Promote AI awareness and adoption within the manufacturing organization.
- Identify site AI competency and training requirements.
- Develop and support a network of AI Champions / Site Enablers / Domain Experts.
- Work with the Workforce Enablement team to support AI upskilling and reskilling.
- Drive adoption of AI-enabled ways of working and help embed AI into daily manufacturing operations.
- Encourage manufacturing teams to progressively identify and initiate AI opportunities independently.
6. Governance & Communication
- Ensure site AI activities comply with AI@BEM portfolio governance, project methodology and standards.
- Provide regular portfolio status, KPI and value reporting to Site Management and AI@BEM governance.
- Represent the site during AI portfolio and Steering Committee reviews.
- Ensure appropriate governance of AI deployment, data usage, solution ownership and sustainability.
- Communicate achievements, issues, risks and support requirements clearly to senior stakeholders.
Role Accountability
The AI Site Lead is accountable for:
- Site AI strategy and roadmap
- Site AI project portfolio
- AI project prioritization
- AI business outcomes
- Business value delivery
- AI deployment and adoption
- Scaling and replication of AI solutions
- Site stakeholder coordination
- Site AI capability development
- Portfolio governance and reporting
The AI Site Lead is not primarily accountable for:
- AI model development
- Data pipeline development
- AI architecture design
- MLOps platform development
- Infrastructure provisioning
These technical activities are delivered in collaboration with Manufacturing Data Science, Data Scientists, Data Engineers, AI Infrastructure and other technical teams.
Candidate Profile
Education
- Minimum Bachelor's Degree in Engineering or a closely related technical discipline.
- Degree in Manufacturing Engineering, Electrical/Electronics Engineering, Mechanical Engineering, Industrial Engineering, Computer Engineering or similar preferred.
- Master's degree in Engineering, Data Science, AI, Business or related discipline is an advantage.
Professional Experience
Minimum requirements:
- At least 5 years of manufacturing experience, preferably within a complex industrial or high-volume manufacturing environment.
- At least 3 years of practical experience working with Data, Analytics, Digital Transformation and/or Artificial Intelligence initiatives.
- Demonstrated experience working within a multinational organization.
- Demonstrated experience working across multiple departments and functions, for example Manufacturing, Engineering, Quality, IT, Data Science and Management.
- Experience leading or coordinating cross-functional projects involving both technical and business stakeholders.
Preferred Experience
- Semiconductor or advanced manufacturing experience.
- Experience deploying AI/analytics solutions into production manufacturing environments.
- Experience in AI use cases such as:
- Computer vision
- Predictive analytics
- Equipment intelligence
- Process optimization
- Yield and quality analytics
- Predictive maintenance
- Intelligent automation
- Project or program management experience.
- Exposure to Data Engineering, MLOps, data governance and AI platforms would be advantageous.
Key Competencies
CompetencyExpected Capability
| Manufacturing Knowledge | Strong understanding of manufacturing processes, equipment, quality, yield and operational KPIs |
| AI & Data Understanding | Able to understand AI/analytics opportunities, requirements, limitations and deployment considerations |
| Business Acumen | Able to translate AI projects into measurable operational and financial value |
| Project Leadership | Able to structure, prioritize and drive multiple AI initiatives |
| Stakeholder Management | Comfortable influencing Engineering, Operations, IT, Quality and Management |
| Change Leadership | Able to drive adoption and new AI-enabled ways of working |
| Communication | Able to communicate technical topics clearly to both technical teams and senior management |
| Problem Solving | Strong analytical approach to manufacturing and business problems |
| Influencing | Able to lead across functions even without direct hierarchical authority |
| Multicultural Collaboration | Able to operate effectively within a multinational and multi-site organization |
ST is proud to be one of the 17 companies certified as a 2026 Global Top Employer and the first and only semiconductor company to achieve this distinction. ST was recognized in this ranking thanks to its continuous improvement approach and stands out particularly in the areas of ethics & integrity, purpose & values, organization & change, business strategy, and performance.
At ST, we endeavor to foster a diverse and inclusive workplace, and we do not tolerate discrimination. We aim to recruit and retain a diverse workforce that reflects the societies around us. We strive for equity in career development, career opportunities, and equal remuneration. We encourage candidates who may not meet every single requirement to apply, as we appreciate diverse perspectives and provide opportunities for growth and learning. Diversity, equity, and inclusion (DEI) is woven into our company culture.
To discover more, visit st.com/careers.
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