LSP USA is seeking Senior Vision Engineers to perform the following duties:
Vision System Design and Optical Engineering
- Lead the design of automated optical inspection (AOI) system architecture for EV battery packaging processes, including camera, lens, lighting, and optical path configuration;
- Configure imaging parameters and perform high precision calibration such as distortion correction, flat field adjustment, illumination uniformity tuning, and optical alignment.
- Perform high precision calibration, including distortion correction, flat field alignment, illumination uniformity tuning, and optical axis verification.
- Apply optical metrology techniques to maintain image stability under varying production conditions (vibration, temperature, material reflectance).
Computer Vision Algorithm Development and Software Integration
- Take lead on developing and refining C++ and Python based inspection algorithms within the vision software framework, including grey-value analysis, contour detection, region-of-interest (ROI)–based edge extraction, and geometric measurement techniques.
- Build image preprocessing pipelines that stabilize detection under reflectivity, low contrast, and changing surface textures.
- Implement and modify Python based classifier scripts to enhance image classification performance and category separation accuracy.
- Adjust classifier thresholds, conditional filtering logic, and ROI parameters to reduce false detection rates and improve overall inspection consistency.
Deep Learning Model Training and Classification Optimization
- Develop, retrain, and optimize deep learning models for AOI, including dataset preparation, labeling, augmentation, and controlled model versioning.
- Retrain models based on newly observed defect types or changes in production materials, preventing classification drift.
- Conduct routine defect reviews and retraining cycles to prevent over detection and under detection, incorporating the latest production data.
- Combine deep learning inference with rule-based computer vision logic to create robust hybrid inspection pipelines capable of distinguishing real defects from cosmetic artifacts.
- Maintain structured datasets, model logs, and release documentation to ensure full traceability.
Automation Integration, Troubleshooting, and Knowledge Transfer
- Integrated vision inspection software with factory automation systems, including PLCs, conveyors, robotic handlers, reject equipment, and MES platforms, ensuring reliable real time system synchronization.
- Verify real-time communication so that inspection results trigger proper automated responses (sorting, tracking, reject actions).
- Analyze inspection logs, image histories, and detection patterns to diagnose over-detection or under-detection issues on active production lines.
- Adjust algorithms, optical settings, classifier thresholds, and system parameters to stabilize performance when materials, lighting, or upstream processes change.
- Provide on site and remote troubleshooting expertise to ensure minimal downtime and continuous system reliability.
- Train and mentor junior engineers and technicians in AOI fundamentals, the company’s proprietary machine vision inspection system, system calibration methods, algorithm logic, and troubleshooting practices.
Qualifications:
- Bachelor’s degree in Computer Science, Electrical Engineering, Mechanical Engineering or a closely related technical field.
- Hands-on experience with industrial camera configuration, optical setup, illumination control, and high-precision calibration for automated optical inspection systems.
- Proficiency in C++ and Python for inspection algorithm development, classifier tuning, deep learning model training, and hybrid workflow integration.
- Strong image processing skills, including ROI measurement, grey-value and contour analysis, geometric evaluation, preprocessing techniques, and dataset engineering.
- Experience in integrating inspection systems with PLC and MES platforms using Ethernet IP, TCP IP, and other real-time industrial communication protocols.
- Demonstrated ability to build hybrid C++ / Python / deep learning inspection pipelines for complex defect detection in fast-paced manufacturing environments.
If interested and qualified, please forward your resume to the following for consideration:
LSP USA, LLC
Attn: HR (Include Ref ID: 2512-1)
2 S Main St
Niles, OH 44446
humanresources@lsp.llc
