Padmi

Senior Equipment & Factory Control Automation Engineer

Location not specifiedPosted 2 months ago
Industrial And Manufacturing EngineeringUnspecified
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About our group

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

About the role - you will

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.

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

About you

Strong problem-solving mindset with the ability to translate complex issues into practical solutions

Excellent communication skills and ability to influence cross-functional teams

Comfortable working in a fast-paced manufacturing environment, including occasional off-shift support as needed

Passion for improving manufacturing through automation, data, and intelligent systems

Collaborative mindset with a willingness to both teach and learn within the team

Your experience includes:

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.

You might also have

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

Location: Our Normandale campus spans two suburbs, Edina, and Bloomington, and serves as the Recording Head development and manufacturing arm of Seagate. Located in the heart of a bustling community, Seagate offers an on-site café, or if you prefer, you can drive to one of many restaurants just minutes away. Need to grab a gift over lunch time? Shopping is abundant in the area. If working out is your thing, the on-site fully equipped fitness center hosts wellness programs, outdoor activities, tournaments, and group workouts. Looking for something more laid back? Reset in one of our meditations rooms or simply take a walk around our indoor walking path. On-site cultural festivals, celebrations and community volunteer opportunities also abound.

The estimated base salary range for this position is $92,310.00 - $131,994.00. The individual salary is based on work location and additional factors, including job-related skills, experience, and relevant education or training.

Seagate offers comprehensive benefits to its eligible employees, including, but not limited to, eligibility to participate in discretionary bonus program, medical, dental, vision, and life insurance, short-and long-term disability, 401(k), employee stock purchase plan, health savings account, dependent care, and healthcare spending accounts. Seagate also offers paid time off, including 12 holidays, flexible time off provided pursuant to Seagate policy, a minimum of 48 hours of paid sick leave, and 16 weeks of paid parental leave. The benefits for this position are based on a full-time schedule for a full calendar year and may differ depending on work location.

Location : Normandale, United States

Travel : None

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