AI Engineer

About the role

Applied Materials is seeking an AI Engineer to design and scale manufacturing data ecosystems that drive real‑time analytics, predictive maintenance, and yield optimization across its semiconductor production facilities. You will work at the intersection of data science, AI/ML, and industrial engineering to deliver production‑grade solutions that accelerate time‑to‑insight.

Key responsibilities

• Architect and scale data ecosystems by ingesting, consolidating, and analyzing structured and unstructured data from plant, supply‑chain, and engineering sources.
• Lead advanced analytics initiatives using statistical, machine learning, and data‑mining techniques (Python, R) to solve complex manufacturing problems such as yield optimization and predictive maintenance.
• Build autonomous, AI‑powered pipelines that orchestrate data ingestion, feature engineering, model execution, and decision‑making at scale.
• Define and optimize data architecture, including acquisition strategies, semantic layers, and scalable models supporting real‑time analytics and digital twins.
• Partner with operations, supply‑chain, and product engineering teams to translate data into actionable business outcomes.

Required profile

• Recognized thought leader in manufacturing data science with deep expertise in advanced analytics, AI/ML, and industrial data systems.
• 10+ years of experience in agent‑based systems, AI orchestration frameworks, and workflow automation.
• Proactive business acumen to anticipate manufacturing, supply‑chain, and regulatory challenges and drive data‑driven improvements.
• Strong problem‑solving skills to tackle ambiguous, high‑impact problems using AI‑driven simulations and optimization models.
• Excellent communication and leadership abilities to influence senior stakeholders and mentor multidisciplinary teams.

Required skills

• Python
• R
• SQL
• Machine learning / AI
• Data engineering and modern data platforms
• Agent‑based systems and workflow automation

What we offer

• Location: Singapore
• Supportive work culture that encourages learning, development, and career growth.
• Comprehensive health, wellbeing, and personal‑growth programs.
• Opportunities to work on cutting‑edge AI solutions that shape the future of semiconductor manufacturing.