AI Development Engineer_ME

Job Description

Job Summary：

Responsible for the design, development and implementation of AI solutions to achieve smart industrialization and manufacturing, including exploring innovative AI applications in industrial and driving manufacturing digital technology promotion.

You will gain a core opportunity to drive digital transformation in manufacturing, deeply leveraging cutting-edge Industry 4.0 and AI technologies to translate business pain points into measurable digital solutions, directly driving significant enhancements in factory operational efficiency and business value while building strategic influence through cross-functional collaboration.

Job Responsibilities：

Technical Development & Implementation

• Develop AI algorithms in directions of agent, knowledge graph, data mining, and potentially computer vision
• Colloborate with frontend development to build full-stack delivery capabilities
• Integrate AI models (machine learning/deep learning/agent/GenAI) into industrial application systems

Technical Research & Innovation

• Track cutting-edge digital technologies (edge computing, digital twin, generative AI, etc.)
• Explore the feasibility of new technologies in manufacturing scenarios, delivering innovative POCs
• Build technical knowledge base and promote continuous improvement of team technical capabilities

Qualifications

• Master Degree in Computer Science, Artificial Intelligence, Software Engineering or related technical fields
• Solid computer science fundamentals (data structures, algorithms, operating systems)
• More than 2 years of AI development experience (manufacturing digital project experience preferred)
• Experience of leading at least 3 complete AI application projects
• Solid understanding of AI agents, including agent architectures, task planning, multi-step reasoning, and tool-use orchestration
• Familiarity with supervised, self-supervised, and reinforcement learning methods; ability to design adaptive agents that improve from feedback or historical data
• Experience combining LLMs with structured data, knowledge bases, and rule-based systems; familiar with RAG (Retrieval-Augmented Generation) pipelines
• Ability to integrate perception and environment feedback into agent decisions, including sensor, vision, log, and time-series data
• Strong software engineering skills, especially in Python; capable of building robust, production-ready agent systems with error handling, logging, and observability
• Excellent communication skills, capable of explaining complex AI/agent concepts to diverse audiences, including non-technical stakeholders
• Collaborative mindset, able to work with robotics engineers, control engineers, and IT/platform teams for scalable agent solutions