Vision Systems Engineer

Coilcraft - Cary, IL

Full-time

Cary, IL

Computer and Electronic Product Manufacturing

About the position

The Vision Systems Engineer at Coilcraft is responsible for designing and developing advanced vision systems for various applications, including object detection, recognition, tracking, and image analysis. This role involves collaboration with cross-functional teams to define system requirements, implementing and optimizing computer vision algorithms, and integrating vision systems into existing products. The engineer will also conduct testing and validation to ensure system reliability and troubleshoot any issues that arise.

Responsibilities

• Design and develop vision systems for a wide range of applications, including object detection, recognition, tracking, and image analysis.
• Collaborate with cross-functional teams to define system requirements and specifications for vision-based projects.
• Implement and optimize computer vision algorithms and models.
• Integrate vision systems into existing products or develop standalone vision solutions, considering hardware and software constraints.
• Conduct thorough testing and validation of vision systems to ensure accuracy, robustness, and reliability.
• Troubleshoot and debug vision system issues, analyzing data and proposing effective solutions.
• Collaborate with hardware engineers to select appropriate sensors, cameras, and other vision-related components.
• Create detailed documentation, including system architecture, specifications, user manuals, and technical reports.
• Stay abreast of industry trends and emerging technologies, actively contributing to the continuous improvement of vision system engineering practices within the organization.

Requirements

• Bachelor's degree in Computer Science, Electrical Engineering, or a related field.
• Proven experience in computer vision development, including object detection, tracking, and image analysis.
• Strong understanding of computer vision algorithms and techniques, including deep learning and convolutional neural networks.
• Familiarity with hardware components used in vision systems, such as cameras, sensors, and lenses.
• Solid knowledge of image processing techniques and related tools.

Nice-to-haves

• Proficiency in programming languages such as Python, C++, or MATLAB is preferred but not required.