Senior Equipment & Factory Control Automation Engineer

Seagate Technology•Bloomington, MN

5d•$92,310 - $131,994•Onsite

About The Position

Equipment Engineering is the backbone of Seagate’s wafer manufacturing excellence. Our team ensures every piece of tooling operates at peak performance to fabricate the Magnetic Recording Heads that power Seagate’s world-class HDDs. We combine deep equipment engineering expertise with advanced factory control systems, sensors, and AI-driven technologies to monitor tool health in real time and enable proactive, automated decision-making. Join Seagate’s Wafer AI vision, where we are transforming traditional manufacturing into a smart factory. You’ll work on high-impact initiatives with measurable ROI, collaborating with global experts across engineering, AI, and operations in a culture that values innovation, continuous learning, and teamwork. This role is ideal for someone who enjoys hands-on equipment work while also building next-generation automation, data systems, and smart factory capabilities. You will bridge traditional equipment engineering with intelligent automation, support, optimize, and modernize semiconductor manufacturing equipment while driving adoption of data-driven control strategies and AI-enabled solutions.

Requirements

Demonstrated Experience in semiconductor or wafer manufacturing equipment
Hands-on experience with equipment systems in areas such as Photolithography, Plating, Metrology, or Inspection
Understanding of equipment performance, reliability, and maintenance practices
Experience with statistical analysis tools (e.g., JMP, Minitab, Six Sigma methodologies)
Proficiency in programming or scripting (e.g., Python, SQL, R, or similar)
Experience or exposure to implementing equipment control strategies or factory automation systems
Bachelor’s degree in engineering related field (i.e. Electrical, Mechanical, Chemical, Computer Engineering, Computer Science, AI/ML, 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.

Nice To Haves

Experience integrating sensors, edge devices, or data acquisition systems into manufacturing equipment
Familiarity with AI/ML concepts applied to equipment monitoring or fault detection
Experience with containerization or ML deployment tools (e.g., Docker, Kubernetes, MLflow)
Background in upgrading legacy tools with modern controls, sensors, or automation capabilities
Exposure to machine vision systems (e.g., OpenCV) or embedded platforms (e.g., Jetson, Raspberry Pi)
Knowledge of SPC, DOE, DMAIC, or structured problem-solving methodologies

Responsibilities

Support development, deployment, and optimization of wafer processing equipment across areas such as Photolithography, Electromagnetic Plating, or Metrology
Lead installation, modification, upgrade, and maintenance of manufacturing equipment to improve performance and reliability
Evaluate equipment health and drive actions to improve uptime, throughput, and process stability
Develop and implement factory control strategies using automation, sensors, and AI-driven monitoring solutions
Deploy data collection systems and integrate tools using software (e.g., Python, SQL, AI frameworks) to enhance tool performance and decision-making
Build or support lightweight AI models and rule-based logic for anomaly detection, predictive maintenance, and automated interlocks
Partner with Equipment, Process, Yield, and Data Engineering teams to solve complex manufacturing issues and identify high-value improvement opportunities
Lead or support root cause investigations using engineering fundamentals, statistical analysis, and data insights
Maintain documentation on tool upgrades, safety issues, and technical notices from equipment suppliers
Provide technical support to technicians, operators, and engineering teams, and contribute to knowledge sharing across the organization