Application Engineer

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

Salary:

$ - $

Location:

Santa Clara,CA

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.

Role Overview

We are looking for an Application Engineer to develop and deploy advanced analytics for complex industrial systems.

In this role, you will work at the intersection of engineering domain knowledge, data analytics, and AI/ML, helping translate operational needs into scalable, production‑ready analytical solutions used in real manufacturing environments.

This is a hands‑on technical role that collaborates closely with product, software, and customer‑facing teams to deliver high‑impact digital solutions from concept to deployment.

Key Responsibilities

* Break down complex engineering problems and unstructured domain knowledge into structured analytical inputs

* Analyze operational data to identify patterns, anomalies, and actionable insights for system performance improvement

* Identify edge cases, gaps, and failure modes in analytical solutions and drive continuous improvements

* Interpret model outputs and translate results into engineering recommendations

* Design, develop, and maintain analytics and algorithmic models for industrial applications

* Prototype new algorithmic approaches and support transition into production software

* Own the performance and reliability of deployed solutions and continuously improve them

* Manage analytics lifecycle activities including validation, versioning, and release readiness

* Validate analytical models against real-world scenarios, including false positive / false negative analysis, and ensure robustness and practical usability before and after deployment

* Work closely with domain experts (e.g., engineering teams) to translate domain knowledge into scalable solutions

* Collaborate with product, software, and field teams to deploy and continuously improve solutions

* Participate in technical requirements definition, prioritization, and schedule alignment

* Produce clear technical documentation, reports, and presentations to support development, validation, and deployment

Required Qualifications

Experience & Background

* Bachelor's degree in Engineering, Computer Science, Data Science or a related field.

* 5+ years of relevant experience with a Bachelor's degree, or 2+ years with a Master's degree, in application engineering, algorithm development, or related technical roles

* Experience in industrial, manufacturing, or complex system environments strongly preferred

* Experience with model/version lifecycle management, release processes, or production software environments

Core Skills

* Self-starter with strong problem-solving skills and a research-oriented mindset

* Ability to translate data insights into practical engineering decisions

* Strong ability to work across engineering, software, and data analytics domains

* Hands-on experience analyzing and working with real-world equipment or operational datasets

* Comfortable working with ambiguous or incomplete problem definitions…