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Job Responsibilities
AI Algorithm Research & Development: Design, develop and optimize AI algorithm models based on specific needs of automated equipment (e.g., precision assembly lines, inspection equipment, logistics sorting systems, predictive maintenance systems).
Model Deployment & Integration: Capable of efficiently deploying trained AI models to edge computing platforms (e.g., industrial computers, embedded systems, GPU-accelerated devices) or industrial PCs of automated equipment.
Data Processing & Feature Engineering: Collect, label, extract and select features of industrial on-site data to build high-quality training and test datasets.
Technical Documentation: Write clear technical documents, including algorithm design documents, test reports, user manuals, etc.
Technology Tracking & Innovation: Follow new research progress and technical trends of AI in industrial automation, and explore its application potential in the company’s products.
Job Requirements
(I) Educational Qualifications
Full-time master’s degree or above in computer science, artificial intelligence, automation, control science and engineering, electronic engineering, mechanical engineering (intelligent direction), applied mathematics or related majors.
(II) Core Technical Competencies
Solid programming foundation, proficient in Python; familiarity with C/C++ is preferred.
In-depth understanding of basic principles of machine learning and deep learning; familiar with mainstream model architectures such as CNN, RNN/LSTM, Transformer.
Proficient in at least one mainstream deep learning framework (e.g., PyTorch, Tensorflow, Keras).
Familiar with basic theories and common algorithms of computer vision (e.g., OpenCV-related algorithms).
Experience in successful deployment and optimization of AI models on embedded platforms (e.g., ARM Cortex-A series).
English Proficiency: CET-4 or above.
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