Controls Engineer

Position Description We are dedicated to designing, manufacturing and selling high quality vehicles that meet the diverse needs of our customers. We believe our employees and the different perspectives that they bring to the business are the driving force behind our success. Come discover a company that is focused on the quality of our vehicles, the environment, the community and the world in which we live. Position Duties Develop and implement improvements to control systems and equipment using Factory Information Systems (FIS) data Lead problem solving in resolving equipment performance issues Lead troubleshooting; coordinate resources to find root cause and fixes, manage and breakdown problems into items that can be validated Assist in the training of manufacturing personnel and plant electricians Assist in integration of controls into IT systems like Factory Information Systems (FIS), Error Proofing, QWX, and QTS. Troubleshoot machinery, robot, automation, and controls issues and downtime Use FIS plant monitoring software to review cycle times of equipment Review and coordinate project installations Reprogram equipment for engineering changes and improvements Maintain program backups for machinery and automation Program new installations of automation, machinery, material handling, and robots Review risk assessments as part of a team evaluating equipment safety Skills Required Access Controls Siemens Backup Software Software Development

PLC/CNC

Robotics Computer Vision Education High School Diploma Experience 5+ years of related experience Ability to work with UAW maintenance, Vendors, and other Process Team Members when required Microsoft Suite familiarity (Excel, PowerPoint, Outlook) PLC Controller experience (Siemens, Rexroth, Allen Bradley) Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for this position. #J-18808-Ljbffr Optimal