Duties & Responsibilities
● To improve the accuracy/yield of the optics and opto-mechanical assembly products, design AI model application solutions, including requirement decomposition and technology selection, and promote the solutions from prototype verification to deployment in production.
● Be responsible for the development of AI models for optical industry (such as optical defect recognition models, optical process parameter optimization models, and optical component performance prediction models).
● Conduct data preprocessing and feature engineering based on the characteristics of optical data, optimize model accuracy, and inference efficiency.
● Integration of data throughout the entire manufacturing process of optics and opto-mechanical assemblies; utilize data mining methods to unearth data value.
● Track the development of cutting-edge AI technologies and data mining tools and investigate the feasibility of implementing new technologies in optical and opto-mechanical manufacturing scenarios.
● Draft technical documents to provide technical support for the engineering and production team.

Qualification & Requirements
● A master's degree or higher, majoring in Computer Science and Technology, Artificial Intelligence, Data Science, Electronic Information Engineering, Optical Engineering, Optoelectronic Information Science and Engineering, or other related fields. Doctoral degree holders are preferred.
● At least 3 years of experience in AI application development, with a minimum of 1 year of experience in technical positions related to the optical manufacturing industry (such as optical communication, lasers, lens development, or optical inspection equipment).
● Proficiency in using AI development tools and data mining tools; have knowledge of AI services on industrial cloud platforms or edge AI deployment tools.
● Proficiency in at least one programming language such as Python, Java, or C++.
● Proficiency in data mining methods (such as association analysis, cluster analysis, regression analysis, and anomaly detection).
● Be familiar with machine learning algorithms, and have knowledge of model fine-tuning, model compression, and image preprocessing technologies.
● Be familiar with big data processing tools and relevant data analysis libraries, and be able to efficiently complete batch data cleaning, transformation, and analysis for optical data.
● Basic optical knowledge (such as geometric optics, fiber optics, principles of optical imaging), understand optical manufacturing processes; be able to quickly understand the workflow of optical manufacturing.
● Proficient in English writing and speaking.
● Be willing to learn new things, knowledge, and ideas.