R&D Engineer 구인
R&D Engineer 구인
by LSP USA, LLC 2024.10.24
LSP USA is an R & D oriented engineering company, specializing in the development, installation, engineering maintenance, sales, and servicing of factory automation equipment and software, leveraging advanced monitoring, real-time process control, and data analysis techniques to ensure seamless operation and optimization of automated factory processes.
LSP USA is seeking skilled and innovative R&D Engineers to join our dynamic team. In this role, you will be responsible for developing cutting-edge machine vision technology for enhanced defect detection and precision in battery cell manufacturing. As a member of an R&D team, comprised of engineers from various fields, you will collaborate with fellow R&D engineers and cross-functional teams of engineers to develop imaging processes, algorithm development, and data-driven solutions for improving defect detection and production quality. The ideal candidate will have a strong background in machine vision systems, image processing, and algorithm development, and a passion for leveraging data to solve challenging defect detection problems.
Job Description
• Research and develop innovative machine vision technologies to enhance defect detection, precision, and quality control in battery cell manufacturing processes.
• Refine image processing and machine learning models to improve the precision of identifying micro-defects in battery cells, ensuring high sensitivity and minimal false positives/negatives.
• Collaborate with cross-functional teams of engineers to integrate machine vision systems into production lines.
• Evaluate and optimize sensor and camera technologies, ensuring they meet performance, speed, and accuracy requirements for high-throughput production environments.
• Collect and preprocess large image datasets of battery cells to train machine learning models that enhance detection accuracy, particularly for critical defects affecting battery performance and safety.
• Implement real-time data analytics to track and assess the performance of machine vision systems, continuously improving defect detection rates through feedback and iteration.
• Conduct experimental trials and analyze data to validate vision system performance, making adjustments to improve accuracy, reliability, and robustness.
Qualifications & Skills
• Bachelor's degree in Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, Robotics and Automation, Software Engineering, Information Engineering, or closely related; Master’s degree in a relevant field is preferred.
• Proficiency in programming languages such as C/C++, Python, MATLAB, or LabVIEW for developing and testing machine vision algorithms.
• Practical experience in training and applying machine learning models (e.g., CNNs) for defect detection and classification in industrial settings.
• Proficient in analyzing large image datasets to improve machine learning models and enhance system performance.
• Strong ability to work with cross-functional teams to ensure successful system integration.
• Ability to quickly adapt to new technologies, tools, and methods, continuously seeking to improve defect detection and system precision.
• Strong skills in documenting research, development processes, and system performance to support future improvements and maintain system reliability.
LSP USA is seeking skilled and innovative R&D Engineers to join our dynamic team. In this role, you will be responsible for developing cutting-edge machine vision technology for enhanced defect detection and precision in battery cell manufacturing. As a member of an R&D team, comprised of engineers from various fields, you will collaborate with fellow R&D engineers and cross-functional teams of engineers to develop imaging processes, algorithm development, and data-driven solutions for improving defect detection and production quality. The ideal candidate will have a strong background in machine vision systems, image processing, and algorithm development, and a passion for leveraging data to solve challenging defect detection problems.
Job Description
• Research and develop innovative machine vision technologies to enhance defect detection, precision, and quality control in battery cell manufacturing processes.
• Refine image processing and machine learning models to improve the precision of identifying micro-defects in battery cells, ensuring high sensitivity and minimal false positives/negatives.
• Collaborate with cross-functional teams of engineers to integrate machine vision systems into production lines.
• Evaluate and optimize sensor and camera technologies, ensuring they meet performance, speed, and accuracy requirements for high-throughput production environments.
• Collect and preprocess large image datasets of battery cells to train machine learning models that enhance detection accuracy, particularly for critical defects affecting battery performance and safety.
• Implement real-time data analytics to track and assess the performance of machine vision systems, continuously improving defect detection rates through feedback and iteration.
• Conduct experimental trials and analyze data to validate vision system performance, making adjustments to improve accuracy, reliability, and robustness.
Qualifications & Skills
• Bachelor's degree in Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, Robotics and Automation, Software Engineering, Information Engineering, or closely related; Master’s degree in a relevant field is preferred.
• Proficiency in programming languages such as C/C++, Python, MATLAB, or LabVIEW for developing and testing machine vision algorithms.
• Practical experience in training and applying machine learning models (e.g., CNNs) for defect detection and classification in industrial settings.
• Proficient in analyzing large image datasets to improve machine learning models and enhance system performance.
• Strong ability to work with cross-functional teams to ensure successful system integration.
• Ability to quickly adapt to new technologies, tools, and methods, continuously seeking to improve defect detection and system precision.
• Strong skills in documenting research, development processes, and system performance to support future improvements and maintain system reliability.