AI Engineer - Manufacturing Data Science

About the role

Applied Materials, a global leader in materials science and engineering solutions for semiconductors and advanced displays, is hiring an AI Engineer in Singapore. The role builds manufacturing data ecosystems and applies advanced analytics and AI to solve complex manufacturing problems such as yield optimization, predictive maintenance and constraint resolution.

Key responsibilities

• Architect and scale manufacturing data ecosystems by ingesting, consolidating and analyzing structured and unstructured data from plant, supply chain and engineering sources.
• Lead analytics and modeling initiatives using statistical, machine learning and data mining techniques (Python, R) for yield optimization, predictive maintenance and constraint resolution.
• Build autonomous, AI-powered pipelines that orchestrate data ingestion, feature engineering, model execution and decision-making at scale.
• Define and optimize data architecture, including data acquisition strategies, semantic layers and scalable data models supporting real-time analytics, digital twins and AI-driven manufacturing use cases.
• Partner with manufacturing operations, supply chain and product engineering teams to define KPIs, uncover insights and operationalize recommendations.
• Develop production-grade analytics solutions using SQL, Python and modern data platforms to process large industrial datasets.
• Enable experimentation and continuous improvement by framing hypotheses, designing experiments and uncovering deeper correlations.
• Communicate complex findings to senior leadership through clear narratives and visualizations.

Required profile

• Thought leader in manufacturing data science, with deep expertise in advanced analytics, AI/ML and industrial data systems, plus cross-domain knowledge of supply chain, quality and engineering.
• 10+ years of experience in agent-based systems, AI orchestration frameworks and workflow automation.
• Business acumen: anticipates manufacturing, supply chain and regulatory challenges and aligns analytics with strategic priorities on cost, throughput, yield and cycle time.
• Solves complex, ambiguous problems with AI-driven simulations, optimization models and graph-based reasoning.
• Influences strategy, investment and resource allocation for analytics and AI programs, and establishes best practices for data products and AI adoption.
• Communicates technical concepts to senior stakeholders and leads and mentors multi-disciplinary teams (data science, engineering, analytics and UI/API).

Required skills

• Python and R
• SQL
• Machine learning and data mining
• Agent-based systems and workflow automation

The position is full time, with travel of about 10% of the time and relocation eligibility. It is an equal opportunity employer.