AI Engineer - (B5)

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. 

What We Offer

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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. 

• 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.

• 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.

• 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.

• 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.

• 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.

• 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

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The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

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.

In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at [email protected], or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.