We are hiring a Director for Physical AI to integrate robotics, physical automation, and AI-driven control logic into Micron's smart manufacturing ecosystem -- enabling autonomous, adaptive, and highly efficient manufacturing operations at scale. You will drive cross-functional transformation, partnering with site and global manufacturing and engineering teams to embed physical AI capabilities seamlessly into production environments.

Job Responsibilities

Lead Micron's Physical AI strategy and delivery across FE and AT manufacturing, including: -

Define and lead Micron's Physical AI vision and roadmap across FE and AT manufacturing, and identify high-impact use cases (material handling, smart dispatching, adaptive automation)
Establish a scalable framework for robotics integration, orchestration, and control logic within Micron's smart manufacturing systems
Drive integration of robotics platforms, AMRs, tool automation, and control systems with SMAI applications and the Micron MES ecosystem
Architect solutions that combine AI/ML models, decision engines, and robotics execution layers, ensuring interoperability across heterogeneous systems and hardware vendors
Lead end-to-end deployment from pilot to high-volume manufacturing (HVM) across global FE/AT sites
Establish best practices for standardisation, scalability, and reliability of physical AI solutions drive adoption and value realisation across sites
Partner with site leadership, central engineering, and supply chain stakeholders to align priorities, translate manufacturing needs into AI/automation solutions, and influence global investment prioritisation
Stay at the forefront of robotics, AI, and autonomous systems innovation drive experimentation with AMRs, digital twins for physical systems, real-time optimisation, and closed-loop control
Co-develop with external partners, vendors, and research organisations on emerging robotics and AI capabilities represent Micron in joint roadmaps
Establish KPIs and report quarterly to executive leadership on Physical AI impact across productivity, cost, cycle time, safety, and inventory across global sites
Work with AI developers team to generate agentic AI workflow where applicable

Lead People and Teams

Build, mentor, and lead a high-performing, multi-disciplinary team spanning data science, robotics, software, and automation engineering
Act as a key interface between technical teams and business leadership, translating manufacturing needs into AI and automation solutions
Exceptional stakeholder management and influencing skills across global organisations comfortable leading in ambiguous, fast-evolving environments
Apply strong systems-thinking and problem-solving capability to deep automation architecture and manufacturing systems decisions
Champion AI literacy and drive organisational change management so fab operators, technicians, and engineers trust and adopt AI-driven robotics
Demonstrate accountability and lead with strategic thinking, strong execution discipline, passion, and integrity

Qualifications

Bachelor's degree in Engineering, Computer Science, Robotics, or related field (Master's or MBA a strong plus)
10+ years of experience in manufacturing, automation, robotics, or AI systems, with proven leadership in large-scale cross-functional programmes
Experience in semiconductor manufacturing (FE and/or AT) environments
Strong background in robotics integration (AMR, AGV, tool automation) and smart manufacturing systems (MES, automation platforms)
Proven track record deploying AI/ML in operational settings, with demonstrated ability to translate complex technical concepts into business impact
Deep understanding of manufacturing systems and automation architecture exceptional influencing skills across global, matrixed organisations
In new product design roles: Provides technical leadership and oversight of the development of integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments. For product/system performance projects: Directs the use of machine language and statistical modeling techniques such as decision trees, logistic regression and Bayesian analysis to develop and evaluate algorithms to improve performance, quality, data management and accuracy. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience. Selects, develops, and evaluates personnel ensuring the efficient operation of the function.

Director, Physical AI, SMAI