AI Engineer

Applied Materials South East Asia; Singapore; On-site; SGD 180,000 - 320,000; Full time

Job summary

Applied Materials Singapore is seeking a senior data scientist/leader to architect and scale manufacturing data ecosystems and drive AI‑driven analytics across plant, supply chain, and engineering domains.

You will lead cross‑functional teams, apply ML and AI techniques, design scalable data models, and translate insights into measurable improvements in yield, throughput, and cycle time for semiconductor manufacturing.

Qualifications

• 10+ years of experience in agent‑based systems, AI orchestration frameworks, and workflow automation.
• Expertise in advanced analytics, AI/ML, and industrial data systems.

Responsibilities

• Architect and scale manufacturing data ecosystems by ingesting, consolidating, and analyzing data from plant, supply chain, and engineering sources.
• Lead analytics and modeling initiatives using statistical, ML, and data mining techniques to optimize yield and predict maintenance.
• Build autonomous, AI-powered pipelines for data ingestion, feature engineering, model execution, and decision making at scale.
• Define data architecture including data acquisition strategies, semantic layers, and scalable data models for real‑time analytics and digital twins.
• Translate data into actionable outcomes by partnering with manufacturing operations, supply chain, and product engineering to define KPIs and drive improvements.
• Design production‑grade analytics solutions leveraging SQL, Python, and modern data platforms for large industrial datasets.
• Collaborate with product, engineering, and operations to frame hypotheses, run experiments, and uncover deeper correlations.
• Communicate insights to senior leadership with clear narratives and visualizations to influence strategy.

Skills

Advanced analytics

AI/ML

Data architecture

Industrial data systems

Cross-domain knowledge

Tools

SQL

Python

R

Job description

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer

Location:

Singapore,SGP

You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.

Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

Key Responsibilities

• Architect and scale manufacturing data ecosystems by designing and implementing robust methods, processes, and systems to ingest, consolidate, and analyze structured and unstructured data from diverse plant, supply chain, and engineering sources.
• Lead advanced analytics and modeling initiatives by applying statistical, machine learning, and data mining techniques (Python, R) to solve complex manufacturing problems such as yield optimization, predictive maintenance, and constraint resolution.
• Drive agentic workflows and intelligent automation by building autonomous, AI-powered pipelines that orchestrate data ingestion, feature engineering, model execution, and decision-making at scale, reducing manual intervention and accelerating time-to-insight.
• Define and optimize data architecture including data acquisition strategies, semantic layers, and scalable data models that support real‑time analytics, digital twins, and AI‑driven manufacturing use cases.
• Translate data into actionable business outcomes by partnering closely with manufacturing operations, supply chain, and product engineering teams to define KPIs, uncover insights, and operationalize recommendations.
• Develop production‑grade analytics solutions by designing algorithms, models, and automation pipelines leveraging SQL, Python, and modern data platforms to cleanse, integrate, and process large‑scale industrial datasets.
• Enable experimentation and continuous improvement by collaborating with product, engineering, and operations teams to frame hypotheses, design experiments, and uncover deeper correlations that extend beyond current measurement systems.
• Communicate insights with executive impact by translating complex analytical findings into clear, compelling narratives and visualizations that influence senior leadership decision‑making and operational strategies.

Functional Expertise

• Recognized as a thought leader in manufacturing data science, with deep expertise in advanced analytics, AI/ML, and industrial data systems, complemented by strong cross‑domain knowledge (supply chain, quality, engineering).
• 10+ years of experience in agent‑based systems, AI orchestration frameworks, and workflow automation, enabling scalable and reusable analytics solutions.

Business Acumen

• Proactively anticipates manufacturing, supply chain, and regulatory challenges, recommending data‑driven improvements to processes, product quality, and operational efficiency.
• Aligns analytics initiatives with strategic business priorities, driving measurable impact across cost, throughput, yield, and cycle time.

Problem Solving

• Tackles highly complex, ambiguous problems with significant business impact using innovative analytical approaches, including AI‑driven simulations, optimization models, and graph‑based reasoning.
• Designs end‑to‑end intelligent systems that integrate data, models, and decision logic into automated workflows.

Impact

• Influences strategic direction, investment decisions, and resource allocation for analytics and AI programs within manufacturing.
• Establishes best practices for data products, automation frameworks, and AI adoption across global operations.

Interpersonal Leadership

• Effectively communicates complex technical concepts to senior stakeholders, anticipating objections and driving alignment across cross‑functional teams.
• Leads and mentors multi‑disciplinary teams (data science, engineering, analytics, and UI/API) to deliver high‑impact, production‑ready solutions.

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.