Vision Engineer

About the role

The Vision Engineer is responsible for designing, developing, deploying, and sustaining advanced machine vision and automated inspection systems used in CelLink's manufacturing processes. This position combines expertise in industrial machine vision, computer vision, artificial intelligence/machine learning, and software development to create scalable inspection and process-monitoring solutions that improve product quality, yield, equipment performance, and manufacturing efficiency.

The Vision Engineer develops both traditional rule-based and AI-enabled vision applications, including the software, algorithms, data pipelines, interfaces, and system integrations required to deploy these solutions in a high-volume manufacturing environment.

Essential Duties & Responsibilities

• Design, develop, deploy, and optimize machine vision and computer vision systems, including cameras, optics, lighting, image acquisition, calibration, image-processing algorithms, inspection logic, measurement, defect detection, classification, and automated pass/fail decisions.
• Develop production software and applications supporting vision and inspection systems using languages and technologies such as Python, C#, C++, SQL, APIs, databases, and related development frameworks; maintain robust source control, testing, documentation, deployment, and software revision practices.
• Develop and deploy AI/ML-based computer vision solutions for defect detection, anomaly detection, classification, measurement, and process monitoring, including data preparation, model training, validation, deployment, performance monitoring, and continuous improvement.
• Integrate vision systems and software with manufacturing equipment and factory systems, including PLCs, motion systems, MES, databases, SPC, traceability systems, and other production data platforms to enable automated decisions, data collection, analytics, and closed-loop process improvement.
• Own vision system performance throughout the equipment lifecycle, including requirements development, vendor technical reviews, FAT/SAT, commissioning, qualification, troubleshooting, root-cause analysis, false reject/false accept reduction, documentation, training, and sustained production support.

Minimum Qualifications

• BS in Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, Mechatronics, Robotics, Optical Engineering, or a related technical field.
• 3+ years of hands-on experience developing, integrating, or supporting industrial machine vision, automated optical inspection, computer vision, or image-processing systems in a manufacturing or automation environment.
• Hands-on experience with industrial cameras, lenses, lighting, image acquisition, calibration, and image-processing techniques.
• Programming experience using Python, C#, C++, or similar languages for machine vision, automation, or manufacturing applications.
• Experience troubleshooting automated equipment and integrating vision systems with industrial controls, PLCs, or production equipment.

Preferred Qualifications

• Experience developing production software using Python, C#, C++, SQL, or similar technologies.
• Experience with software architecture, APIs, databases, source/version control, automated testing, and deployment practices.
• Experience with computer vision frameworks and libraries such as OpenCV, PyTorch, TensorFlow, or equivalent technologies.
• Experience developing, training, validating, and deploying AI/ML models for industrial computer vision applications.
• Experience with industrial vision platforms such as Cognex, Keyence, Basler, Teledyne, Omron, or similar systems.
• Experience integrating software and vision applications with PLCs, MES, databases, SPC, traceability, and manufacturing data systems.
• Experience developing software and vision solutions for high-volume automated manufacturing equipment.
• Experience with statistical methods including GR&R, measurement-system analysis, process capability, and validation of automated inspection systems.

Knowledge, Skills & Abilities

• Strong knowledge of industrial machine vision principles, including cameras, sensors, lenses, field of view, depth of field, resolution, exposure, triggering, lighting, optics, and image quality.
• Strong knowledge of image-processing techniques including filtering, thresholding, edge detection, feature extraction, pattern matching, measurement, segmentation, and defect classification.
• Knowledge of AI/ML computer vision techniques, including model development, training, validation, deployment, and performance monitoring in a production environment.
• Strong programming and debugging skills with the ability to develop maintainable production-level vision applications and tools.
• Ability to translate product specifications and quality requirements into reliable automated inspection criteria.
• Strong troubleshooting and root-cause analysis skills across software, controls, optics, lighting, mechanical systems, and manufacturing processes.
• Working knowledge of industrial automation, PLC communications, networking, databases, and manufacturing data systems.
• Ability to analyze inspection and production data to distinguish actual product/process variation from measurement-system variation and communicate technical information effectively across functions.

Additional information

We believe diversity and inclusion among our teammates are essential to our success. We celebrate diversity and are committed to creating an inclusive environment for all employees while building teams that represent a variety of backgrounds, perspectives, and skills. All employment is decided based on qualifications, merit, and business needs.

CelLink was founded in 2012 and entered volume production in 2018. CelLink provides electrical systems to the world's leading automotive OEMs & EV manufacturers, data center developers, and stationary power companies. The company has raised approximately $315M in funding through private investment and multiple grants from the US Department of Energy. CelLink's investors include 3M, Atreides, BMW, BorgWarner, Bosch, D1 Capital, Fidelity, Fontinalis Partners, Ford, Franklin Templeton, Lear, Park West, SK Telecom, Standard Investments, T. Rowe Price, Tinicum, and Whale Rock.