Factory Control and Automation Senior Engineer
Listed on 2026-02-06
-
Engineering
Robotics, Systems Engineer, AI Engineer, Electrical Engineering
Factory Control and Intelligent Automation Senior Engineer
Location:
Bloomington, MN, US
Posting Date:
Jan 26, 2026
Job
About our group:Equipment Engineering is the backbone of Seagate’s wafer manufacturing excellence. Our team ensures every piece of tooling on the factory floor operates at peak performance to fabricate the Magnetic Recording Heads that power Seagate’s world‑class HDDs.
We combine proven equipment‑control strategies with cutting‑edge KPIV streamline systems to monitor equipment health in real time and take proactive, automated actions.
Join us and be part of Seagate’s Wafer AI 2.0 vision: scaling AI to revolutionize wafer operations. Work on high‑impact projects with measurable ROI—Seagate’s AI initiatives have already saved millions. Collaborate with global experts in AI, engineering, and operations. Enjoy a dynamic, inclusive culture that values innovation, agility, and continuous learning.
About the role - you will:- Work as a Factory Control and Intelligent Automation Engineer, together with Equipment Engineering in Seagate’s advanced wafer manufacturing team, where you’ll be at the forefront of smart factory transformation.
- Thrive in this role if you are passionate about automation, robotics, and next‑generation smart factory systems
- Lead efforts to build intelligent control systems, integrate sensor technologies, and translating innovative AI capabilities into robust, scalable controls systems that redefine operational excellence.
- Lead development and integration of intelligent control systems within production equipment and fab support systems.
- Deploy sensors, edge devices, and AI powered monitoring logic to enhance real time equipment health awareness.
- Build and maintain lightweight AI agents for anomaly detection, sensor validation, data conditioning, and automated interlocks.
- Collaborate with Equipment, Process, Yield, and Data Engineering teams to identify high‑value opportunities for automation and AI adoption.
- Support digitalization and hardware retrofit initiatives to enable data capture and closed‑loop automation on legacy tools.
- Drive structured root cause investigations combining hardware expertise, data analytics, and AI generated insights.
- Ensure solutions are robust, safe, maintainable, and aligned with factory control standards and change control procedures.
- Proficiency in Python, ML frameworks (e.g., MLflow, KServe), and containerization tools (Docker, Kubernetes).
- Excellent engineering, problem‑solving, communication, and project management skills.
- Strong written and verbal skills; ability to persuade and gain agreement with cross‑functional teams.
- Passion for transforming traditional manufacturing through intelligent systems and data‑driven insights.
- Interest or experience in tool automation or robotics is a plus.
- Deep understanding on semiconductor equipment hardware & controls and how their KPIV/KPOV signals reflect tool health and process stability.
- Experience in integrating sensors or edge modules into production tools.
- Experience using Python, Bash, or Power Shell for data modeling and automated control actions.
- Experience applying lightweight ML techniques—such as rule‑based intelligence, or simple classifiers—to improve equipment reliability and automated decision logic.
- Demonstrated commitment to staying current with new AI techniques, sensor technologies, and intelligent automation trends—and applying them meaningfully in a fab environment.
- Bachelor’s degree in engineering related field (i.e. Electrical, Mechanical, Chemical, Computer Engineering, Materials, Physics, or Information Technology) and 5+ years of experience or master’s degree in the same and 3+ years’ experience or PhD and 0+ years’ experience or equivalent experience and education.
- Familiarity with using cameras for alignment, endpoint monitoring, wear detection, or component verification, using practical OpenCV or edge inference workflows.
- Exposure to deploy logic or models on industrial gateways, microcontrollers, or platforms like Jetson/Raspberry Pi for real‑time hardware interaction.
- Background in adding sensors, upgrading interlocks, or…
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