Sr. Equipment Engineer - Automation & Smart Manufacturing

Seagate Technology•Bloomington, MN

33d•$94,140 - $134,625•Onsite

About The Position

The Equipment Engineering team is helping lead Seagate's transformation to an AI-enabled smart factory. Our engineers combine advanced manufacturing equipment, automation, predictive analytics, and data-driven engineering to deliver the performance, reliability, and innovation needed to produce the world's most advanced magnetic recording heads. As demand for AI continues to grow, so does the need for high-capacity data storage. Our team plays a critical role in enabling that future by designing and implementing smarter ways to monitor, optimize, and improve complex manufacturing systems. This is far more than a traditional equipment engineering role. We leverage advanced factory control systems, AI-driven monitoring, predictive analytics, and automation to improve equipment performance before problems occur. Working alongside Manufacturing, Process Engineering, Automation, Quality, and Data Science teams, you'll help shape the future of one of the industry's most advanced wafer manufacturing operations. If you enjoy solving difficult technical problems, influencing how manufacturing technology evolves, and making a measurable impact on factory performance, we'd love to hear from you. As a Senior Equipment Engineer, you'll own the technical performance, reliability, and continuous improvement of some of Seagate's most advanced manufacturing equipment, including photolithography, electroplating, and precision metrology systems operating in a cleanroom environment. This is a highly visible, hands-on engineering role where you'll combine technical expertise, data analytics, automation, and cross-functional leadership to improve equipment reliability, increase manufacturing throughput, and enable next-generation data storage technology. You'll spend time both on the manufacturing floor solving challenging technical problems and using data, automation, and AI-driven tools to eliminate recurring failures before they impact production.

Requirements

Bachelor's Degree in Electrical Engineering, Mechanical Engineering, Chemical Engineering, Computer Engineering, Materials Science, Physics, Information Technology, or a related engineering field and 5+ years of experience, or Master’s degree in the same fields and 3+ years of experience, or PhD and 0+ years of experience or equivalent education and experience.
Hands-on experience troubleshooting, optimizing, and improving complex manufacturing equipment.
Strong electrical and mechanical troubleshooting skills.
Experience using statistical analysis tools such as JMP, Minitab, SPC, DOE, Six Sigma, or similar methodologies.
Experience applying Root Cause Analysis (RCA), Failure Mode and Effects Analysis (FMEA), or other reliability engineering methodologies.
Demonstrated ability to improve equipment performance, reliability, throughput, and manufacturing productivity through data-driven decision making.
Experience working with equipment control strategies, factory automation systems, Manufacturing Execution Systems (MES), or related manufacturing technologies.

Nice To Haves

Experience leveraging AI or machine learning tools to improve equipment performance, automate monitoring, or optimize manufacturing operations.
Semiconductor or wafer fabrication experience, particularly with photolithography, electroplating, metrology, or similar process equipment.
Experience with Lean Manufacturing, TPM, DMAIC, Reliability Centered Maintenance (RCM), or other continuous improvement methodologies.
Knowledge of robotics, motion control, PLCs, sensors, machine vision, and industrial networking.
Experience developing dashboards, automated monitoring tools, or analytics solutions using SQL, Python, Power BI, or similar technologies.
Six Sigma Green Belt or Black Belt certification.

Responsibilities

Own the technical performance, reliability, and long-term evolution of advanced wafer fabrication equipment.
Lead complex troubleshooting efforts, identify root causes, and implement permanent corrective actions that improve equipment reliability and performance.
Analyze equipment data using statistical tools to identify opportunities to improve throughput, reduce scrap, increase uptime, and eliminate recurring issues.
Develop and implement AI-driven equipment monitoring and predictive maintenance strategies that improve factory performance.
Drive equipment upgrades, new tool installations, automation initiatives, and capital improvement projects that expand manufacturing capability.
Partner closely with technicians, Process Engineering, Manufacturing, Automation, Quality, and fellow Equipment Engineers to solve complex technical challenges.
Build strong working relationships across multiple organizations while providing technical leadership and mentoring less experienced engineers and technicians.
Influence equipment strategy by identifying opportunities to improve automation, equipment reliability, operational efficiency, and smart factory capabilities.
Occasionally provide technical leadership during major equipment installations, critical factory events, or complex troubleshooting activities.